[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"seo-content-skill-python-in":3,"job-search-\u002Fen-in\u002Fjobs-by-skill\u002Fpython?page=3":33,"skill-page-filters-\u002Fen-in\u002Fjobs-by-skill\u002Fpython?page=3":738,"featured-jobs-\u002Fen-in\u002Fjobs-by-skill\u002Fpython?page=3":947},{"image_path":4,"content_de":5,"content_en":18,"composite_key":31,"last_updated":32},"\u002Fimages\u002Fskill\u002Fpython.webp",{"tab1":6,"tab2":9,"tab3":12,"tab4":15},{"title":7,"content":8},"Bedeutung & Relevanz","Die Bedeutung von [Python](\u002Fjobs-by-skill\u002Fpython) in [Indien](\u002Fsearch) hat in den letzten Jahren exponentiell zugenommen. Als vielseitige Programmiersprache spielt Python eine entscheidende Rolle in der digitalen Transformation der indischen Finanzindustrie. Insbesondere im Bereich [Asset Management](\u002Fjobs-by-industry\u002Fasset-management) und [Financial Services](\u002Fjobs-by-industry\u002Ffinancial-services) ermöglicht Python die Automatisierung komplexer Prozesse und die Entwicklung innovativer Finanzlösungen.\n\nIn [Indien](\u002Fsearch) wird Python intensiv für Datenanalyse, maschinelles Lernen und die Entwicklung von Finanzanwendungen genutzt. Die Sprache bietet eine robuste Grundlage für die Implementierung von [Generative AI](\u002Fjobs-by-skill\u002Fgenerative-ai) und [Artificial Intelligence Tools](\u002Fjobs-by-skill\u002Fartificial-intelligence-tools), die in der modernen Finanzwelt unverzichtbar geworden sind. Unternehmen wie Allianz Insurance setzen auf Python-basierte Lösungen für Risikomanagement und Portfolioptimierung.\n\nDie strategische Relevanz von Python zeigt sich besonders in der Fähigkeit, komplexe finanzielle Modelle zu erstellen und große Datenmengen effizient zu verarbeiten. Dies macht Python zu einer Schlüsselkompetenz für Fachkräfte, die in der dynamischen indischen Finanzbranche erfolgreich sein möchten.",{"title":10,"content":11},"Top-Branchen & Standorte","In [Indien](\u002Fsearch) konzentriert sich die Nachfrage nach Python-Kenntnissen auf mehrere Schlüsselbranchen und Standorte. Die Versicherungsbranche, insbesondere [Insurance](\u002Fjobs-by-industry\u002Finsurance) und [Insurance and Financial Services](\u002Fjobs-by-industry\u002Finsurance-and-financial-services), gehört zu den Hauptarbeitgebern für Python-Entwickler. Ebenso ist [Asset Management](\u002Fjobs-by-industry\u002Fasset-management) eine bedeutende Branche, die Python für Portfolioanalyse und Risikomanagement einsetzt.\n\nGeografisch gesehen sind [Pune](\u002Fsearch) und [Mumbai](\u002Fsearch) die führenden Standorte für Python-Profis in [Indien](\u002Fsearch). Diese Metropolen beherbergen zahlreiche Finanzinstitute und Technologieunternehmen, die Python für die Entwicklung innovativer Finanzlösungen nutzen. Die Kombination aus [Banking](\u002Fjobs-by-industry\u002Fbanking) und Technologie macht diese Städte zu idealen Orten für Python-Experten.\n\nWeitere wichtige Branchen umfassen [Financial Services](\u002Fjobs-by-industry\u002Ffinancial-services) und [Asset Management Financial Services](\u002Fjobs-by-industry\u002Fasset-management-financial-services), wo Python für die Automatisierung von Geschäftsprozessen und die Entwicklung von Handelsalgorithmen eingesetzt wird. Die Konzentration auf diese Branchen und Standorte bietet Python-Profis in [Indien](\u002Fsearch) exzellente Karrieremöglichkeiten.",{"title":13,"content":14},"Gefragte Skills & Arbeitgeber","Führende Unternehmen in [Indien](\u002Fsearch) wie Allianz Insurance und CO_ANT-MUM Annet Technologies Mumbai LLP suchen aktiv nach Python-Experten mit spezifischen Kompetenzen. Diese Arbeitgeber erwarten umfassende Kenntnisse in [DevOps Practices](\u002Fjobs-by-expertise\u002Fdevops-practices), [Agile Methodologies](\u002Fjobs-by-expertise\u002Fagile-methodologies) und [Risk Management](\u002Fjobs-by-expertise\u002Frisk-management).\n\nBesonders gefragt sind Expertise in [Financial Analysis](\u002Fjobs-by-expertise\u002Ffinancial-analysis) und [Financial Modeling](\u002Fjobs-by-expertise\u002Ffinancial-modeling), kombiniert mit Python-Kenntnissen. Weitere wichtige Bereiche umfassen [System Reliability](\u002Fjobs-by-expertise\u002Fsystem-reliability), [Incident Management](\u002Fjobs-by-expertise\u002Fincident-management) und [Performance Optimization](\u002Fjobs-by-expertise\u002Fperformance-optimization). Die Integration von Python mit [Cloud Infrastructure Automation](\u002Fjobs-by-expertise\u002Fcloud-infrastructure-automation) und [Event-Driven Architecture](\u002Fjobs-by-expertise\u002Fevent-driven-architecture) ist ebenfalls hochrelevant.\n\nUnternehmen wie Allianz Insurance setzen Python für [Portfolio Management](\u002Fjobs-by-expertise\u002Fportfolio-management) und [Risk Assessment](\u002Fjobs-by-expertise\u002Frisk-assessment) ein, während Technologiefirmen wie CO_ANT-MUM Annet Technologies Mumbai LLP die Sprache für die Entwicklung von Finanzsoftware und Automatisierungslösungen nutzen. Die Kombination aus Python und [Financial Markets](\u002Fjobs-by-expertise\u002Ffinancial-markets)-Expertise ist besonders wertvoll.",{"title":16,"content":17},"Karriere & Entwicklung","Die Karrierewege für Python-Experten in [Indien](\u002Fsearch) sind vielfältig und vielversprechend. Einsteiger können als Python-Entwickler in Finanzinstituten beginnen und sich zu Spezialisten für [Financial Analysis](\u002Fjobs-by-expertise\u002Ffinancial-analysis) oder [Data Analytics](\u002Fjobs-by-expertise\u002Fdata-analytics) entwickeln. Fortgeschrittene Karrierepfade führen zu Positionen wie Data Scientist, Quant-Analyst oder Finanzsoftware-Architekt.\n\nUm Python effektiv zu erlernen, sollten angehende Entwickler zunächst Grundlagen wie [SQL](\u002Fjobs-by-skill\u002Fsql) und [MS Excel](\u002Fjobs-by-skill\u002Fms-excel) beherrschen. Die Integration mit Technologien wie [Kubernetes](\u002Fjobs-by-skill\u002Fkubernetes), [AWS](\u002Fjobs-by-skill\u002Faws) und [Docker](\u002Fjobs-by-skill\u002Fdocker) ist essentiell für moderne Anwendungen. Kenntnisse in [CI\u002FCD Pipelines](\u002Fjobs-by-skill\u002Fci-cd-pipelines) und [Git](\u002Fjobs-by-skill\u002Fgit) verbessern die Entwicklungseffizienz erheblich.\n\nDie Kombination von Python mit [Machine Learning](\u002Fjobs-by-skill\u002Fmachine-learning) und [Generative AI](\u002Fjobs-by-skill\u002Fgenerative-ai) eröffnet besonders zukunftsträchtige Perspektiven. Fachkräfte sollten sich kontinuierlich in Bereichen wie [Cloud Computing](\u002Fjobs-by-skill\u002Fcloud-computing), [System Monitoring](\u002Fjobs-by-skill\u002Fsystem-monitoring) und [Automation Scripting](\u002Fjobs-by-skill\u002Fautomation-scripting) weiterbilden, um wettbewerbsfähig zu bleiben. Praktische Erfahrung mit [Financial Modeling](\u002Fjobs-by-expertise\u002Ffinancial-modeling) und [Risk Management](\u002Fjobs-by-expertise\u002Frisk-management) rundet das Profil ab.",{"tab1":19,"tab2":22,"tab3":25,"tab4":28},{"title":20,"content":21},"Strategic Importance","Python has emerged as a cornerstone technology in India's rapidly evolving financial landscape, particularly within the insurance and financial services sectors. Its versatility and extensive library ecosystem make it indispensable for developing sophisticated automation solutions, data analytics platforms, and financial technology applications. In India, where digital transformation is accelerating, Python enables companies like Allianz Insurance and CO_ANT-MUM Annet Technologies Mumbai LLP to streamline operations, enhance customer experiences, and drive innovation in areas such as fund administration and cross-jurisdictional services. The language's simplicity and scalability support the implementation of [Generative AI](\u002Fjobs-by-skill\u002Fgenerative-ai) and [Artificial Intelligence Tools](\u002Fjobs-by-skill\u002Fartificial-intelligence-tools), which are critical for competitive differentiation. As financial institutions increasingly adopt cloud infrastructure and [Automation Solutions](\u002Fjobs-by-expertise\u002Fautomation-solutions), Python's role in scripting, data processing, and system integration becomes paramount, ensuring robust, efficient, and secure financial ecosystems tailored to India's dynamic market demands.",{"title":23,"content":24},"Top Industries & Locations","In India, Python is highly sought after in key industries such as [Insurance](\u002Fjobs-by-industry\u002Finsurance), [Insurance and Asset Management](\u002Fjobs-by-industry\u002Finsurance-and-asset-management), [Insurance and Financial Services](\u002Fjobs-by-industry\u002Finsurance-and-financial-services), and [Financial Services](\u002Fjobs-by-industry\u002Ffinancial-services). These sectors leverage Python for tasks ranging from data analysis and financial modeling to automation and software development, aligning with the country's push toward digitalization. Geographically, demand is concentrated in major hubs like [Pune](\u002Fsearch) and [Mumbai](\u002Fsearch), where a thriving tech ecosystem supports innovation in financial services technology. These locations host numerous companies driving Python adoption for applications in [Cloud Computing](\u002Fjobs-by-skill\u002Fcloud-computing), [System Monitoring](\u002Fjobs-by-skill\u002Fsystem-monitoring), and [Web Application Development](\u002Fjobs-by-expertise\u002Fweb-application-development), making them prime areas for professionals skilled in Python to find opportunities in roles that require cross-functional collaboration and adherence to compliance standards like [SOX Compliance](\u002Fjobs-by-expertise\u002Fsox-compliance) and [GDPR Compliance](\u002Fjobs-by-expertise\u002Fgdpr-compliance).",{"title":26,"content":27},"In-Demand Skills & Employers","Top companies in India, including [Allianz Insurance](\u002Fcompany\u002Fallianz-insurance) and [CO_ANT-MUM Annet Technologies Mumbai LLP](\u002Fcompany\u002Fco_ant-mum-annet-technologies-mumbai-llp), seek Python expertise to support a range of specialized functions. These employers value professionals who combine Python with [DevOps Practices](\u002Fjobs-by-expertise\u002Fdevops-practices), [Agile Methodologies](\u002Fjobs-by-expertise\u002Fagile-methodologies), and [Risk Mitigation](\u002Fjobs-by-expertise\u002Frisk-mitigation) to enhance system reliability and incident management. Key related expertises in demand include [System Reliability](\u002Fjobs-by-expertise\u002Fsystem-reliability), [Performance Optimization](\u002Fjobs-by-expertise\u002Fperformance-optimization), and [Site Reliability Engineering](\u002Fjobs-by-expertise\u002Fsite-reliability-engineering), which are essential for maintaining robust IT infrastructure. Additionally, skills in [Financial Analysis](\u002Fjobs-by-expertise\u002Ffinancial-analysis) and [Financial Modeling](\u002Fjobs-by-expertise\u002Ffinancial-modeling) are often paired with Python to drive data-driven decision-making. Employers also prioritize knowledge in [Security Best Practices](\u002Fjobs-by-expertise\u002Fsecurity-best-practices) and [Compliance Management](\u002Fjobs-by-expertise\u002Fcompliance-management), ensuring that Python applications meet regulatory requirements like [ISO 27001 Compliance](\u002Fjobs-by-expertise\u002Fiso-27001-compliance) in India's stringent financial environment.",{"title":29,"content":30},"Career & Development","A career leveraging Python in India offers diverse paths, from roles in software development and data engineering to specialized positions in financial technology and [Asset Management](\u002Fjobs-by-industry\u002Fasset-management). To build expertise, professionals should focus on mastering Python alongside [TOP RELATED IT SKILLS](\u002Fjobs-by-skill\u002Ftop-related-it-skills) such as [Kubernetes](\u002Fjobs-by-skill\u002Fkubernetes), [AWS](\u002Fjobs-by-skill\u002Faws), and [Azure](\u002Fjobs-by-skill\u002Fazure), which are critical for cloud-based applications. Learning [CI\u002FCD Pipelines](\u002Fjobs-by-skill\u002Fci-cd-pipelines) and tools like [Docker](\u002Fjobs-by-skill\u002Fdocker) and [Git](\u002Fjobs-by-skill\u002Fgit) enhances capabilities in automation and [Software Development](\u002Fjobs-by-expertise\u002Fsoftware-development). For advancement, combining Python with [Data Analytics](\u002Fjobs-by-expertise\u002Fdata-analytics) and [Machine Learning](\u002Fjobs-by-skill\u002Fmachine-learning) opens doors to roles in [Generative AI](\u002Fjobs-by-skill\u002Fgenerative-ai) and [Artificial Intelligence](\u002Fjobs-by-skill\u002Fartificial-intelligence), areas of growing importance in India. Engaging in continuous learning through certifications and hands-on projects in [System Integration](\u002Fjobs-by-expertise\u002Fsystem-integration) and [Cloud Infrastructure Automation](\u002Fjobs-by-expertise\u002Fcloud-infrastructure-automation) can lead to opportunities in top industries, supporting career growth in Pune, Mumbai, and beyond while adhering to evolving [Security Protocols](\u002Fjobs-by-expertise\u002Fsecurity-protocols) and digitalization trends.","skill:python:in","2026-08-17T09:01:41.503922+02:00",{"total":34,"jobs":35},275,[36,95,177,232,262,294,309,322,352,380,411,448,481,523,559,597,627,655,669,710],{"id":37,"slug":38,"title":39,"raw_title":40,"is_featured":41,"company":42,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":45,"processed_country_iso_code_gmaps":47,"processed_home_office":49,"processed_salary_min":50,"processed_salary_max":51,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":54,"processed_employment_types":56,"processed_it_skills":57,"processed_it_skills_labels":61,"processed_job_expertise_skills":81,"processed_job_expertise_skills_labels":82,"max_cpc":94,"actual_cpc":94},88193,"senior-software-engineerjava-hartford-global-services-private-limited","Senior Software Engineer\u002FJava",null,false,{"name":43,"slug":44,"logo_url":40},"Hartford Global Services Private Limited","hartford-global-services-private-limited",[46],"Hyderabad",[48],"IN","onsite",2500000,4000000,"INR","estimated",[55],"FULL_TIME","permanent",{"aws":58,"git":59,"jms":59,"sql":59,"java":58,"rest":59,"soap":59,"rally":60,"github":59,"ibm mq":59,"python":59,"angular":59,"jenkins":59,"sonarqube":60,"terraform":59,"spring batch":60,"generative ai":60,"cloudformation":59,"google cloud platform":60},4,3,2,[62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80],"Java","Angular","AWS","Python","SQL","Terraform","CloudFormation","JMS","IBM MQ","GitHub","Jenkins","Rally","SonarQube","SOAP","REST","Git","Generative AI","Google Cloud Platform","Spring Batch",{"ci\u002Fcd":58,"devops":58,"monitoring":59,"cloud migration":58,"hybrid integrations":58,"infrastructure as code":58,"security implementation":59,"guidewire insurancesuite":60,"web services development":59,"messaging and integration":58,"resiliency implementation":59},[83,84,85,86,87,88,89,90,91,92,93],"Cloud Migration","Messaging and Integration","Infrastructure as Code","CI\u002FCD","DevOps","Security Implementation","Resiliency Implementation","Monitoring","Hybrid Integrations","Web Services Development","Guidewire InsuranceSuite",1,{"id":96,"slug":97,"title":98,"raw_title":40,"is_featured":41,"company":99,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":102,"processed_country_iso_code_gmaps":104,"processed_home_office":105,"processed_salary_min":106,"processed_salary_max":107,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":108,"processed_employment_types":56,"processed_it_skills":109,"processed_it_skills_labels":110,"processed_job_expertise_skills":153,"processed_job_expertise_skills_labels":154,"max_cpc":94,"actual_cpc":94},83099,"gcp-full-stack-data-ai-engineer-as-f337-deutsche-india-private-limited-pune-branch","GCP Full-Stack Data & AI Engineer, AS",{"name":100,"slug":101,"logo_url":40},"F337 Deutsche India Private Limited, Pune Branch","f337-deutsche-india-private-limited-pune-branch",[103],"Pune",[48],"hybrid",2000000,3500000,[55],{"git":58,"iam":58,"jwt":58,"sql":58,"cors":58,"ci\u002Fcd":58,"flask":58,"owasp":58,"react":58,"docker":58,"pytest":58,"python":58,"angular":58,"fastapi":58,"postman":58,"pub\u002Fsub":59,"bigquery":58,"cloud run":58,"cloud sql":59,"firestore":59,"oauth 2.0":58,"rest apis":58,"terraform":58,"embeddings":58,"guardrails":59,"javascript":58,"typescript":58,"cloud build":58,"memorystore":59,"api gateways":58,"cloud storage":58,"dialogflow cx":58,"gemini models":58,"rate limiting":58,"apache airflow":59,"cloud composer":59,"openid connect":58,"secret manager":58,"cx agent studio":58,"human oversight":59,"input validation":58,"vector databases":58,"artifact registry":58,"secrets management":58,"google cloud platform":58,"google cloud operations":58,"agent-to-agent protocols":59,"multi-agent orchestration":59,"google agent development kit (adk)":58},[65,66,111,112,113,63,114,115,116,79,117,118,119,120,121,122,123,124,125,126,77,127,67,128,129,86,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152],"JavaScript","TypeScript","React","FastAPI","Flask","REST APIs","Cloud Run","BigQuery","Cloud Storage","Secret Manager","Cloud Composer","Apache Airflow","Pub\u002FSub","Cloud SQL","Firestore","Memorystore","Docker","Artifact Registry","Cloud Build","OAuth 2.0","OpenID Connect","JWT","IAM","API gateways","CORS","rate limiting","secrets management","input validation","OWASP","Postman","Pytest","Google Cloud Operations","Gemini models","embeddings","vector databases","Dialogflow CX","CX Agent Studio","Google Agent Development Kit (ADK)","multi-agent orchestration","agent-to-agent protocols","guardrails","human oversight",{"devops":58,"agentic ai":58,"data lineage":58,"data quality":58,"generative ai":58,"orchestration":58,"ai engineering":58,"data modelling":58,"responsible ai":58,"data governance":58,"data engineering":58,"capacity planning":58,"incident response":58,"secure publishing":58,"cloud architecture":58,"query optimization":58,"architecture design":58,"quality engineering":58,"security engineering":58,"software engineering":58,"full-stack development":58,"technical documentation":58,"operations & reliability":58,"batch and streaming design":58},[155,156,157,158,159,87,160,161,162,78,163,164,165,166,167,168,169,170,171,172,173,174,175,176],"Software Engineering","Full-Stack Development","Data Engineering","AI Engineering","Cloud Architecture","Quality Engineering","Security Engineering","Operations & Reliability","Agentic AI","Technical Documentation","Architecture Design","Incident Response","Capacity Planning","Data Modelling","Batch and Streaming Design","Orchestration","Data Quality","Data Lineage","Data Governance","Query Optimization","Secure Publishing","Responsible AI",{"id":178,"slug":179,"title":180,"raw_title":40,"is_featured":41,"company":181,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":184,"processed_country_iso_code_gmaps":186,"processed_home_office":105,"processed_salary_min":187,"processed_salary_max":188,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":189,"processed_employment_types":56,"processed_it_skills":190,"processed_it_skills_labels":191,"processed_job_expertise_skills":203,"processed_job_expertise_skills_labels":204,"max_cpc":94,"actual_cpc":94},83172,"xtrackers-sea-order-cr-sr-tech-analyst-automation-avp-e901-dws-india-private-limited-bangalore-branch","Xtrackers SEA - Order C\u002FR (Sr. Tech Analyst, Automation), AVP",{"name":182,"slug":183,"logo_url":40},"E901 DWS India Private Limited, Bangalore Branch","e901-dws-india-private-limited-bangalore-branch",[185],"Bangalore",[48],3000000,5000000,[55],{"mq":59,"git":59,"sql":59,"java":58,"kafka":59,"linux":59,"nosql":59,"gradle":59,"python":58,"jenkins":59,"ai tools":59,"teamcity":59,"playwright":58,"cucumber bdd":58,"rest assured":58,"restful apis":58},[62,65,192,193,194,77,72,195,196,197,66,198,199,200,201,202],"Playwright","Cucumber BDD","REST Assured","TeamCity","Gradle","Linux","NoSQL","Kafka","MQ","RESTful APIs","AI tools",{"bdd":58,"tdd":58,"agile":58,"ci\u002Fcd":58,"scrum":58,"mocking":58,"fixtures":58,"ethical ai":59,"test plans":58,"reliability":58,"code reviews":58,"load testing":58,"test strategy":58,"stress testing":58,"ai productivity":59,"data validation":58,"defect tracking":58,"test automation":58,"database testing":58,"metrics and kpis":58,"software quality":58,"quality assurance":58,"test environments":58,"integration testing":58,"performance testing":58,"automation frameworks":58,"continuous improvement":58,"engineering excellence":58},[205,206,207,208,209,86,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231],"Test Automation","Quality Assurance","Performance Testing","Load Testing","Stress Testing","TDD","BDD","Agile","Scrum","Code Reviews","Database Testing","Data Validation","Integration Testing","Mocking","Fixtures","Test Environments","Automation Frameworks","Test Strategy","Test Plans","Defect Tracking","Metrics and KPIs","Software Quality","Reliability","Continuous Improvement","Engineering Excellence","AI Productivity","Ethical AI",{"id":233,"slug":234,"title":235,"raw_title":40,"is_featured":41,"company":236,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":237,"processed_country_iso_code_gmaps":238,"processed_home_office":105,"processed_salary_min":187,"processed_salary_max":188,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":239,"processed_employment_types":56,"processed_it_skills":240,"processed_it_skills_labels":241,"processed_job_expertise_skills":246,"processed_job_expertise_skills_labels":247,"max_cpc":94,"actual_cpc":94},83098,"gcp-data-and-ai-engineer-avp-f337-deutsche-india-private-limited-pune-branch","GCP Data and AI Engineer, AVP",{"name":100,"slug":101,"logo_url":40},[103],[48],[55],{"aws":59,"gcp":58,"sql":58,"azure":59,"ci\u002Fcd":58,"docker":58,"python":58,"pub\u002Fsub":58,"bigquery":58,"cloud run":58,"rest apis":58,"terraform":58,"vertex ai":58,"cloud build":58,"dialogflow cx":58,"apache airflow":58,"cloud composer":58,"artifact registry":58,"gemini enterprise agent platform":58,"google agent development kit (adk)":58},[65,66,242,118,121,122,117,67,86,129,128,127,116,243,146,244,148,123,245,64],"GCP","Vertex AI","Gemini Enterprise Agent Platform","Azure",{"llms":58,"agentops":58,"etl testing":58,"rag systems":58,"data modeling":58,"generative ai":58,"system design":58,"data engineering":58,"embedding models":58,"vector databases":58,"agentic workflows":58,"conversational ai":58,"query optimization":58,"distributed systems":58,"multi-agent systems":58,"infrastructure as code":58,"security and governance":58,"ai application development":58},[157,248,78,249,250,251,252,253,174,85,254,255,256,257,258,259,260,261],"AI Application Development","RAG Systems","Agentic Workflows","System Design","Distributed Systems","Data Modeling","Security and Governance","ETL Testing","Conversational AI","LLMs","Vector Databases","Embedding Models","Multi-agent Systems","AgentOps",{"id":263,"slug":264,"title":265,"raw_title":40,"is_featured":41,"company":266,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":267,"processed_country_iso_code_gmaps":268,"processed_home_office":105,"processed_salary_min":269,"processed_salary_max":50,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":270,"processed_employment_types":56,"processed_it_skills":271,"processed_it_skills_labels":272,"processed_job_expertise_skills":282,"processed_job_expertise_skills_labels":283,"max_cpc":94,"actual_cpc":94},83106,"sql-developer-as-f337-deutsche-india-private-limited-pune-branch","SQL Developer, AS",{"name":100,"slug":101,"logo_url":40},[103],[48],1500000,[55],{"etl":59,"gcs":59,"git":59,"sql":58,"java":59,"github":59,"pl\u002Fsql":58,"python":59,"sap bo":60,"pub\u002Fsub":59,"tableau":60,"ai tools":60,"bigquery":59,"cloudsql":59,"bitbucket":59,"cloud run":59,"data modeling":59,"google cloud platform":59,"query performance tuning":59},[66,273,65,62,79,274,275,118,117,123,276,277,77,71,278,279,253,280,281],"PL\u002FSQL","GCS","CloudSQL","Tableau","SAP BO","Bitbucket","ETL","Query Performance Tuning","AI Tools",{"scrum":59,"kanban":59,"reporting":60,"data validation":59,"sql development":58,"version control":59,"quality assurance":59,"cloud technologies":59,"data visualization":60,"database migration":59,"agile methodologies":59,"relational databases":58,"data distribution techniques":59},[284,285,286,287,216,206,288,213,289,290,291,292,293],"SQL Development","Relational Databases","Data Distribution Techniques","Database Migration","Agile Methodologies","Kanban","Version Control","Data Visualization","Reporting","Cloud Technologies",{"id":295,"slug":296,"title":297,"raw_title":40,"is_featured":41,"company":298,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":299,"processed_country_iso_code_gmaps":300,"processed_home_office":105,"processed_salary_min":187,"processed_salary_max":188,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":301,"processed_employment_types":56,"processed_it_skills":302,"processed_it_skills_labels":303,"processed_job_expertise_skills":304,"processed_job_expertise_skills_labels":305,"max_cpc":94,"actual_cpc":94},83093,"gcp-data-ai-engineer-as-f337-deutsche-india-private-limited-pune-branch","GCP Data & AI Engineer, AS",{"name":100,"slug":101,"logo_url":40},[103],[48],[55],{"aws":60,"gcp":58,"sql":58,"llms":58,"azure":60,"ci\u002Fcd":58,"docker":58,"python":58,"bigquery":58,"cloud run":58,"rest apis":58,"terraform":58,"cloud build":58,"dialogflow cx":58,"apache airflow":58,"cloud composer":58,"embedding models":58,"vector databases":58,"artifact registry":58,"gemini enterprise agent platform":58,"google agent development kit (adk)":58},[65,66,242,118,121,122,117,67,86,129,128,127,116,146,244,148,258,259,257,245,64],{"etl testing":58,"rag systems":58,"generative ai":58,"system design":58,"data engineering":58,"agentic workflows":58,"conversational ai":58,"production support":58,"ml model deployment":58,"infrastructure as code":58,"security and governance":58,"data pipeline development":58,"ai application development":58},[157,248,251,78,249,250,256,306,307,255,85,254,308],"ML Model Deployment","Data Pipeline Development","Production Support",{"id":310,"slug":311,"title":297,"raw_title":40,"is_featured":41,"company":312,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":313,"processed_country_iso_code_gmaps":314,"processed_home_office":105,"processed_salary_min":187,"processed_salary_max":188,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":315,"processed_employment_types":56,"processed_it_skills":316,"processed_it_skills_labels":317,"processed_job_expertise_skills":318,"processed_job_expertise_skills_labels":319,"max_cpc":94,"actual_cpc":94},83095,"gcp-data-ai-engineer-as-f337-deutsche-india-private-limited-pune-branch-2",{"name":100,"slug":101,"logo_url":40},[103],[48],[55],{"aws":59,"gcp":58,"sql":58,"llms":58,"azure":59,"ci\u002Fcd":58,"docker":58,"python":58,"bigquery":58,"cloud run":58,"rest apis":58,"terraform":58,"cloud build":58,"dialogflow cx":58,"apache airflow":58,"cloud composer":58,"embedding models":58,"vector databases":58,"artifact registry":58,"gemini enterprise agent platform":58,"google agent development kit (adk)":58},[65,66,242,118,121,122,117,67,86,129,128,127,116,146,244,148,258,259,257,245,64],{"agentops":58,"system design":58,"data engineering":58,"conversational ai":58,"production support":58,"generative ai systems":58,"infrastructure as code":58,"security and governance":58,"ai application development":58,"agentic ai application development":58},[157,248,251,256,320,321,261,85,254,308],"Generative AI Systems","Agentic AI Application Development",{"id":323,"slug":324,"title":325,"raw_title":40,"is_featured":41,"company":326,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":329,"processed_country_iso_code_gmaps":331,"processed_home_office":49,"processed_salary_min":332,"processed_salary_max":333,"processed_salary_currency":334,"processed_salary_source":53,"processed_working_hours":335,"processed_employment_types":56,"processed_it_skills":336,"processed_it_skills_labels":337,"processed_job_expertise_skills":343,"processed_job_expertise_skills_labels":344,"max_cpc":94,"actual_cpc":94},88244,"associate-performance-analytics-tiaa-global-capabilities-private-limited","Associate - Performance & Analytics",{"name":327,"slug":328,"logo_url":40},"TIAA Global Capabilities Private Limited","tiaa-global-capabilities-private-limited",[330],"Mumbai",[48],60000,90000,"USD",[55],{"r":59,"sql":59,"excel":59,"python":59,"tableau":59,"power bi":59,"statistical software":59,"data visualization tools":59},[65,66,338,276,339,340,341,342],"R","Power BI","Excel","Data Visualization Tools","Statistical Software",{"statistics":58,"data mining":58,"data analytics":58,"data engineering":59,"project management":59,"predictive modeling":58,"statistical modeling":58,"business intelligence":58},[345,346,347,348,157,349,350,351],"Data Analytics","Statistical Modeling","Predictive Modeling","Data Mining","Business Intelligence","Statistics","Project Management",{"id":353,"slug":354,"title":355,"raw_title":40,"is_featured":41,"company":356,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":359,"processed_country_iso_code_gmaps":361,"processed_home_office":49,"processed_salary_min":362,"processed_salary_max":363,"processed_salary_currency":334,"processed_salary_source":53,"processed_working_hours":364,"processed_employment_types":56,"processed_it_skills":365,"processed_it_skills_labels":366,"processed_job_expertise_skills":373,"processed_job_expertise_skills_labels":374,"max_cpc":94,"actual_cpc":94},85579,"vp-p4-lead-software-eng-job-level-vice-president-morgan-stanley-advantage-svcs","VP , P4, Lead Software Eng : Job Level - Vice President",{"name":357,"slug":358,"logo_url":40},"Morgan Stanley Advantage Svcs","morgan-stanley-advantage-svcs",[360],"Bengaluru",[48],150000,250000,[55],{"kdb":59,"sql":59,"java":58,"python":58,"spring":59,"ag grid":59,"mongodb":59,"angular 2":59,"elasticsearch":59},[62,65,367,368,369,66,370,371,372],"Spring","MongoDB","Elasticsearch","KDB","Angular 2","AG Grid",{"credit trading":59,"business acumen":59,"team management":58,"software development":58,"commodities post trade":59},[375,376,377,378,379],"Software Development","Commodities Post Trade","Credit Trading","Team Management","Business Acumen",{"id":381,"slug":382,"title":383,"raw_title":40,"is_featured":41,"company":384,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":387,"processed_country_iso_code_gmaps":388,"processed_home_office":49,"processed_salary_min":389,"processed_salary_max":390,"processed_salary_currency":334,"processed_salary_source":53,"processed_working_hours":391,"processed_employment_types":56,"processed_it_skills":392,"processed_it_skills_labels":393,"processed_job_expertise_skills":397,"processed_job_expertise_skills_labels":398,"max_cpc":94,"actual_cpc":94},80753,"associate-director-technical-business-analyst-apollo-india-services-llp-2","Associate Director – Technical Business Analyst",{"name":385,"slug":386,"logo_url":40},"Apollo India Services LLP","apollo-india-services-llp",[330],[48],120000,180000,[55],{"sql":59,"python":60,"ai tools":59,"automated testing":59,"database management":59,"automated build and deployment":59},[66,65,281,394,395,396],"Automated Testing","Automated Build and Deployment","Database Management",{"vpm":59,"geneva":59,"fund finance":59,"asset servicing":59,"batch processing":59,"agile development":58,"business analysis":58,"project management":58,"sdlc methodologies":58,"system integration":58,"investment accounting":58,"requirement gathering":58,"middle office operations":59},[399,400,401,402,351,403,404,405,406,407,408,409,410],"SDLC Methodologies","Investment Accounting","Requirement Gathering","Business Analysis","Agile Development","System Integration","VPM","Geneva","Batch Processing","Fund Finance","Asset Servicing","Middle Office Operations",{"id":412,"slug":413,"title":414,"raw_title":40,"is_featured":41,"company":415,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":419,"processed_country_iso_code_gmaps":421,"processed_home_office":105,"processed_salary_min":422,"processed_salary_max":423,"processed_salary_currency":424,"processed_salary_source":53,"processed_working_hours":425,"processed_employment_types":56,"processed_it_skills":426,"processed_it_skills_labels":427,"processed_job_expertise_skills":440,"processed_job_expertise_skills_labels":441,"max_cpc":94,"actual_cpc":94},81733,"consultant-business-analytics-allianz-insurance-2","Consultant-Business Analytics",{"name":416,"slug":417,"logo_url":418},"Allianz Insurance","allianz-insurance","https:\u002F\u002Fcdn.phenompeople.com\u002FCareerConnectResources\u002FAISAIPGB\u002Fimages\u002FHeader-1706868786965.svg",[420],"PUNE",[48],50000,80000,"GBP",[55],{"sql":58,"ci\u002Fcd":59,"mlops":60,"spark":58,"github":59,"python":58,"etl\u002Felt":58,"pyspark":58,"databricks":58,"delta lake":58,"azure synapse":58,"unity catalog":58,"data lakehouse":59,"data modelling":59,"machine learning":60,"feature engineering":60,"distributed data processing":59},[428,429,430,431,432,433,66,65,434,71,86,168,435,436,437,438,439],"Azure Synapse","Databricks","Spark","PySpark","Delta Lake","Unity Catalog","ETL\u002FELT","Data Lakehouse","Distributed Data Processing","MLOps","Feature Engineering","Machine Learning",{"mlops":60,"data security":59,"data pipelines":58,"data governance":59,"data engineering":58,"feature engineering":60,"analytics engineering":58,"data privacy compliance":59,"insurance market knowledge":60,"model lifecycle management":60},[157,442,443,173,444,445,446,437,438,447],"Analytics Engineering","Data Pipelines","Data Security","Data Privacy Compliance","Insurance Market Knowledge","Model Lifecycle Management",{"id":449,"slug":450,"title":451,"raw_title":40,"is_featured":41,"company":452,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":453,"processed_country_iso_code_gmaps":454,"processed_home_office":105,"processed_salary_min":187,"processed_salary_max":188,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":455,"processed_employment_types":56,"processed_it_skills":456,"processed_it_skills_labels":457,"processed_job_expertise_skills":470,"processed_job_expertise_skills_labels":471,"max_cpc":94,"actual_cpc":94},83173,"senior-engineer-avp-e901-dws-india-private-limited-bangalore-branch","Senior Engineer, AVP",{"name":182,"slug":183,"logo_url":40},[185],[48],[55],{"git":59,"sql":58,"java":58,"ci\u002Fcd":59,"kafka":59,"maven":59,"docker":59,"gradle":59,"oracle":58,"python":60,"etl\u002Felt":59,"jenkins":59,"ai tools":60,"rabbitmq":59,"snowflake":59,"jvm tuning":58,"kubernetes":59,"postgresql":58,"spring boot":58,"restful apis":58,"spring cloud":59,"microservices":58,"google cloud platform (gcp)":59,"infrastructure as code (iac)":60},[62,458,459,201,460,461,462,463,464,127,465,199,466,65,77,72,86,467,196,468,66,434,469,202],"Spring Boot","Spring Cloud","Microservices","Oracle","PostgreSQL","Google Cloud Platform (GCP)","Snowflake","Kubernetes","RabbitMQ","Maven","JVM tuning","Infrastructure as Code (IaC)",{"algorithms":59,"agile\u002Fscrum":59,"data structures":59,"data engineering":59,"distributed systems":58,"software engineering":58,"performance optimization":58,"cloud-native architecture":58,"event-driven architectures":59,"database performance tuning":58,"architecture and design principles":59,"site reliability engineering (sre)":59},[155,252,472,473,474,475,476,477,157,478,479,480],"Performance Optimization","Database Performance Tuning","Cloud-Native Architecture","Event-Driven Architectures","Agile\u002FScrum","Site Reliability Engineering (SRE)","Architecture and Design Principles","Algorithms","Data Structures",{"id":482,"slug":483,"title":484,"raw_title":40,"is_featured":41,"company":485,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":486,"processed_country_iso_code_gmaps":487,"processed_home_office":105,"processed_salary_min":51,"processed_salary_max":488,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":489,"processed_employment_types":56,"processed_it_skills":490,"processed_it_skills_labels":491,"processed_job_expertise_skills":505,"processed_job_expertise_skills_labels":506,"max_cpc":94,"actual_cpc":94},83092,"full-stack-reporting-lead-vp-f337-deutsche-india-private-limited-pune-branch","Full Stack Reporting Lead, VP",{"name":100,"slug":101,"logo_url":40},[103],[48],6000000,[55],{"api":58,"gcs":58,"axiom":58,"kafka":59,"uflow":58,"oracle":58,"python":60,"pub\u002Fsub":58,"reactjs":58,"ai tools":60,"bigquery":58,"dataflow":58,"postgres":58,"cloud run":58,"core java":58,"kubernetes":58,"springboot":58,"cdc patterns":59,"cloud composer":58,"cloud functions":58,"spark streaming":59,"messaging technologies":59,"google cloud platform (gcp)":58,"wolter kluwer's application suite":58},[461,492,493,494,495,496,497,463,274,118,123,498,121,117,499,465,199,500,501,502,503,504,65,202],"Postgres","Axiom","Wolter Kluwer's application suite","Core Java","Springboot","ReactJs","Dataflow","Cloud Functions","Spark Streaming","CDC patterns","Messaging technologies","API","uFlow",{"agile":58,"ci\u002Fcd":58,"devops":58,"automation":58,"data lineage":58,"data quality":58,"data modeling":58,"observability":58,"risk management":58,"data engineering":58,"data integration":58,"cloud-native design":58,"metadata management":58,"regulatory reporting":58,"solution architecture":58,"technology governance":58,"event-driven solutions":58,"low-latency processing":58,"master data management":58,"platform modernization":58,"streaming architecture":58,"enterprise reporting architecture":58,"asset management business processes":58},[507,508,157,509,253,510,171,172,511,512,513,514,87,86,515,516,517,518,519,520,521,212,522],"Data Integration","Solution Architecture","Enterprise Reporting Architecture","Metadata Management","Master Data Management","Event-driven solutions","Streaming architecture","Low-latency processing","Automation","Observability","Platform modernization","Technology governance","Risk management","Asset Management business processes","Regulatory Reporting","Cloud-Native design",{"id":524,"slug":525,"title":526,"raw_title":40,"is_featured":41,"company":527,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":528,"processed_country_iso_code_gmaps":529,"processed_home_office":105,"processed_salary_min":269,"processed_salary_max":50,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":530,"processed_employment_types":56,"processed_it_skills":531,"processed_it_skills_labels":532,"processed_job_expertise_skills":545,"processed_job_expertise_skills_labels":546,"max_cpc":94,"actual_cpc":94},83088,"service-operations-production-support-engineer-f337-deutsche-india-private-limited-pune-branch","Service Operations - Production Support Engineer",{"name":100,"slug":101,"logo_url":40},[103],[48],[55],{"gcp":59,"rpa":60,"sql":59,"apis":59,"ci\u002Fcd":59,"mssql":59,"geneos":59,"oracle":59,"python":59,"splunk":59,"grafana":59,"control-m":59,"java j2ee":59,"new relic":59,"openshift":59,"agentic ai":60,"kubernetes":59,"powershell":59,"unix\u002Flinux":59,"microservices":59},[533,534,65,535,66,461,536,242,537,538,539,540,541,460,542,86,543,465,163,544],"UNIX\u002FLinux","Java J2EE","PowerShell","MSSQL","Geneos","Splunk","Grafana","New Relic","Control-M","APIs","OpenShift","RPA",{"automation":59,"bcp testing":59,"itil practices":58,"change management":59,"resiliency events":59,"problem management":59,"sli\u002Fslo definition":59,"incident management":58,"root cause analysis":58,"ai tools for productivity":59,"global transaction banking":60,"site reliability engineering":58,"application performance monitoring":59},[547,548,549,550,551,552,553,554,515,555,556,557,558],"ITIL practices","Site Reliability Engineering","SLI\u002FSLO definition","Incident management","Root cause analysis","Change management","Problem management","Application performance monitoring","Global Transaction Banking","BCP testing","Resiliency events","AI tools for productivity",{"id":560,"slug":561,"title":562,"raw_title":40,"is_featured":41,"company":563,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":564,"processed_country_iso_code_gmaps":565,"processed_home_office":105,"processed_salary_min":187,"processed_salary_max":188,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":566,"processed_employment_types":56,"processed_it_skills":567,"processed_it_skills_labels":568,"processed_job_expertise_skills":575,"processed_job_expertise_skills_labels":576,"max_cpc":94,"actual_cpc":94},88189,"ind-senior-staff-software-engineer-hartford-global-services-private-limited-4","IND Senior Staff Software Engineer",{"name":43,"slug":44,"logo_url":40},[46],[48],[55],{"aws":59,"c++":58,"gcp":59,"git":59,"java":58,"azure":59,"docker":59,"mlflow":59,"python":58,"crew ai":58,"kubeflow":59,"langgraph":58,"semantic kernel":58},[65,62,569,64,245,242,570,571,127,77,572,573,574],"C++","MLflow","Kubeflow","LangGraph","Crew AI","Semantic Kernel",{"llmops":58,"edge ai":59,"ai ethics":59,"statistics":59,"mathematics":59,"generative ai":59,"vector search":58,"explainable ai":59,"bias mitigation":59,"computer vision":59,"data structures":58,"knowledge graph":58,"ai\u002Fml algorithms":58,"graph algorithms":58,"foundation models":59,"prompt engineering":58,"agent orchestration":58,"information retrieval":58,"reinforcement learning":59,"computational neuroscience":59,"model lifecycle management":58,"natural language processing":59,"real-time inference systems":59,"software engineering principles":58},[577,480,578,579,580,447,581,582,583,584,585,586,587,588,78,589,590,591,592,350,593,594,595,596],"AI\u002FML Algorithms","Software Engineering Principles","Agent Orchestration","LLMOps","Vector Search","Information Retrieval","Graph Algorithms","Knowledge Graph","Prompt Engineering","Natural Language Processing","Computer Vision","Reinforcement Learning","Foundation Models","Real-time Inference Systems","Edge AI","Mathematics","Computational Neuroscience","AI Ethics","Bias Mitigation","Explainable AI",{"id":598,"slug":599,"title":600,"raw_title":40,"is_featured":41,"company":601,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":604,"processed_country_iso_code_gmaps":605,"processed_home_office":105,"processed_salary_min":187,"processed_salary_max":188,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":606,"processed_employment_types":56,"processed_it_skills":607,"processed_it_skills_labels":608,"processed_job_expertise_skills":616,"processed_job_expertise_skills_labels":617,"max_cpc":94,"actual_cpc":94},83179,"lender-finance-eu-associate-9608-deutsche-india-private-limited-mumbai-branch","Lender Finance EU - Associate",{"name":602,"slug":603,"logo_url":40},"9608 Deutsche India Private Limited, Mumbai Branch","9608-deutsche-india-private-limited-mumbai-branch",[330],[48],[55],{"sql":58,"vba":58,"ai\u002Fml":59,"python":58,"tableau":59,"ms excel":58,"power bi":59,"data automation":59,"etl (power query)":59,"predictive analytics":59,"large-scale data processing":59},[65,66,609,610,611,339,276,612,613,614,615],"MS Excel","VBA","ETL (Power Query)","AI\u002FML","Predictive Analytics","Data Automation","Large-scale Data Processing",{"underwriting":58,"data analysis":58,"deal monitoring":58,"risk monitoring":58,"financial modeling":59,"asset due diligence":58,"data reconciliation":58,"portfolio analytics":58,"structured transactions":59},[618,619,620,621,622,623,624,625,626],"Data Analysis","Asset Due Diligence","Deal Monitoring","Data Reconciliation","Portfolio Analytics","Risk Monitoring","Underwriting","Financial Modeling","Structured Transactions",{"id":628,"slug":629,"title":630,"raw_title":40,"is_featured":41,"company":631,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":634,"processed_country_iso_code_gmaps":635,"processed_home_office":105,"processed_salary_min":187,"processed_salary_max":188,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":636,"processed_employment_types":56,"processed_it_skills":637,"processed_it_skills_labels":638,"processed_job_expertise_skills":641,"processed_job_expertise_skills_labels":642,"max_cpc":94,"actual_cpc":94},83090,"dws-senior-risk-analyst-model-validation-e902-dws-india-private-limited-maharashtra-branch","DWS Senior Risk Analyst – Model Validation",{"name":632,"slug":633,"logo_url":40},"E902 DWS India Private Limited, Maharashtra Branch","e902-dws-india-private-limited-maharashtra-branch",[103],[48],[55],{"r":59,"c++":58,"sas":59,"sql":59,"matlab":59,"python":58},[338,66,569,639,65,640],"SAS","MATLAB",{"backtesting":59,"capital markets":58,"risk management":58,"model validation":58,"portfolio theory":58,"model development":58,"valuation methods":58,"regulatory guidance":59,"technical documentation":58,"benchmark model building":59,"ai tools for productivity":59,"quantitative risk management":58,"asset classes (fx, rates, equities)":58},[643,644,645,646,647,648,649,650,651,652,653,164,654],"Quantitative Risk Management","Model Validation","Model Development","Valuation Methods","Capital Markets","Portfolio Theory","Risk Management","Asset Classes (FX, Rates, Equities)","Regulatory Guidance","Backtesting","Benchmark Model Building","AI Tools for Productivity",{"id":656,"slug":657,"title":658,"raw_title":40,"is_featured":41,"company":659,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":660,"processed_country_iso_code_gmaps":661,"processed_home_office":49,"processed_salary_min":269,"processed_salary_max":50,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":662,"processed_employment_types":56,"processed_it_skills":663,"processed_it_skills_labels":664,"processed_job_expertise_skills":666,"processed_job_expertise_skills_labels":667,"max_cpc":94,"actual_cpc":94},88185,"ind-senior-staff-net-pythonangular-full-stack-engineer-hartford-global-services-private-limited","IND Senior Staff .NET\u002F Python\u002FAngular Full Stack Engineer",{"name":43,"slug":44,"logo_url":40},[46],[48],[55],{".net":58,"python":58,"angular":58},[665,65,63],".NET",{"full stack development":58},[668],"Full Stack Development",{"id":670,"slug":671,"title":672,"raw_title":40,"is_featured":41,"company":673,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":674,"processed_country_iso_code_gmaps":675,"processed_home_office":49,"processed_salary_min":269,"processed_salary_max":50,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":676,"processed_employment_types":56,"processed_it_skills":677,"processed_it_skills_labels":678,"processed_job_expertise_skills":699,"processed_job_expertise_skills_labels":700,"max_cpc":94,"actual_cpc":94},88243,"associate-full-stack-developer-tiaa-global-capabilities-private-limited","Associate - Full Stack Developer",{"name":327,"slug":328,"logo_url":40},[330],[48],[55],{"s3":58,"aws":58,"ec2":58,"jpa":59,"sql":58,"apis":58,"java":59,"kafka":59,"lambda":58,"pl\u002Fsql":58,"python":58,"aws glue":58,"debugging":59,"etl tools":58,"terraform":58,"cloudwatch":58,"programming":58,"spring boot":59,"devops tools":58,"data analysis":59,"etl pipelines":58,"ci\u002Fcd pipelines":58,"shell scripting":58,"data integration":58,"agile methodology":59,"web application development":59,"operating systems management":59,"software development life cycle":59,"enterprise application integration":59,"continuous integration and deployment":58},[64,679,680,681,682,683,684,685,686,67,66,273,65,687,688,62,458,689,199,542,690,691,692,618,693,694,695,696,697,698],"EC2","S3","AWS Glue","ETL pipelines","CloudWatch","Lambda","DevOps tools","CI\u002FCD pipelines","Shell scripting","ETL tools","JPA","Data integration","Agile Methodology","Continuous Integration and Deployment","Debugging","Enterprise Application Integration","Operating Systems Management","Programming","Software Development Life Cycle","Web Application Development",{"settlement":58,"front office":58,"middle office":58,"data workflows":58,"reconciliation":58,"accounting systems":58,"cloud architecture":58,"financial workflows":58,"full stack development":58,"trade lifecycle management":58,"financial reporting standards":58},[668,159,701,702,703,704,705,706,707,708,709],"Financial Workflows","Trade Lifecycle Management","Settlement","Reconciliation","Accounting Systems","Front Office","Middle Office","Data Workflows","Financial Reporting Standards",{"id":711,"slug":712,"title":713,"raw_title":40,"is_featured":41,"company":714,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":717,"processed_country_iso_code_gmaps":718,"processed_home_office":49,"processed_salary_min":106,"processed_salary_max":107,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":719,"processed_employment_types":56,"processed_it_skills":720,"processed_it_skills_labels":721,"processed_job_expertise_skills":722,"processed_job_expertise_skills_labels":723,"max_cpc":94,"actual_cpc":737},83157,"data-controls-associate-f335-deutsche-india-private-limited-bangalore-branch","Data Controls, Associate",{"name":715,"slug":716,"logo_url":40},"F335 Deutsche India Private Limited, Bangalore Branch","f335-deutsche-india-private-limited-bangalore-branch",[185],[48],[55],{"sql":59,"excel":59,"python":59,"ai tools":59},[65,66,340,281],{"automation":59,"data analysis":58,"documentation":58,"kpi reporting":59,"cash management":58,"swift messaging":58,"payments systems":58,"business analysis":58,"quality assurance":59,"dashboard creation":59,"project management":59,"data reconciliation":58,"incident management":58,"process improvement":58,"anti-financial crime":58,"operations management":58,"regulatory compliance":58,"transaction filtering":58,"transaction monitoring":58},[724,725,726,727,402,618,728,729,730,731,732,733,734,351,621,735,736,206,515],"Operations Management","Cash Management","Payments Systems","SWIFT Messaging","Transaction Monitoring","Transaction Filtering","Anti-Financial Crime","Regulatory Compliance","Incident Management","Process Improvement","Documentation","KPI Reporting","Dashboard Creation",0.3,{"industry":739,"employment_type":791,"expertise_skills":795,"it_skills":864,"salary_currency":933,"processed_working_hours":943},[740,744,748,752,756,760,764,768,771,774,777,780,782,785,788],{"key":741,"label":742,"count":743},"financial services","Financial Services",125,{"key":745,"label":746,"count":747},"financial markets infrastructure","Financial Markets Infrastructure",90,{"key":749,"label":750,"count":751},"data","Data",57,{"key":753,"label":754,"count":755},"insurance","Insurance",42,{"key":757,"label":758,"count":759},"data provider","Data Provider",33,{"key":761,"label":762,"count":763},"asset management","Asset Management",16,{"key":765,"label":766,"count":767},"banking","Banking",6,{"key":769,"label":770,"count":59},"alternative investments","Alternative Investments",{"key":772,"label":773,"count":60},"financial market infrastructure","Financial Market Infrastructure",{"key":775,"label":776,"count":60},"data services","Data Services",{"key":778,"label":779,"count":94},"fund administration","Fund Administration",{"key":781,"label":707,"count":94},"middle office",{"key":783,"label":784,"count":94},"investment","Investment",{"key":786,"label":787,"count":94},"investment banking","Investment Banking",{"key":789,"label":790,"count":94},"alternative asset management","Alternative Asset Management",[792],{"key":56,"label":793,"count":794},"PERMANENT",273,[796,800,802,806,809,812,814,817,820,822,824,827,830,834,837,839,843,845,849,851,854,857,859,861],{"key":797,"label":798,"slug":797,"count":799},"devops","Devops",36,{"key":801,"label":157,"slug":801,"count":799},"data-engineering",{"key":803,"label":804,"slug":803,"count":805},"root-cause-analysis","Root Cause Analysis",35,{"key":807,"label":618,"slug":807,"count":808},"data-analysis",34,{"key":810,"label":649,"slug":810,"count":811},"risk-management",32,{"key":813,"label":515,"slug":813,"count":811},"automation",{"key":815,"label":288,"slug":815,"count":816},"agile-methodologies",31,{"key":818,"label":732,"slug":818,"count":819},"incident-management",26,{"key":821,"label":439,"slug":821,"count":819},"machine-learning",{"key":823,"label":173,"slug":823,"count":819},"data-governance",{"key":825,"label":516,"slug":825,"count":826},"observability",25,{"key":828,"label":829,"slug":828,"count":826},"project-management","Project management",{"key":831,"label":832,"slug":831,"count":833},"cicd","Ci\u002FCd",23,{"key":835,"label":548,"slug":835,"count":836},"site-reliability-engineering",21,{"key":838,"label":253,"slug":838,"count":836},"data-modeling",{"key":840,"label":841,"slug":840,"count":842},"performance-tuning","Performance Tuning",20,{"key":844,"label":585,"slug":844,"count":842},"prompt-engineering",{"key":846,"label":847,"slug":846,"count":848},"generative-ai","Generative Ai",19,{"key":850,"label":171,"slug":850,"count":848},"data-quality",{"key":852,"label":853,"slug":852,"count":848},"infrastructure-as-code","Infrastructure As Code",{"key":855,"label":166,"slug":855,"count":856},"incident-response",17,{"key":858,"label":83,"slug":858,"count":856},"cloud-migration",{"key":860,"label":733,"slug":860,"count":856},"process-improvement",{"key":862,"label":734,"slug":862,"count":863},"documentation",15,[865,867,870,874,877,879,882,886,889,892,895,898,901,904,907,910,912,915,918,920,923,925,928,931],{"key":866,"label":65,"slug":866,"count":34},"python",{"key":868,"label":66,"slug":868,"count":869},"sql",157,{"key":871,"label":872,"slug":871,"count":873},"aws","Aws",85,{"key":875,"label":67,"slug":875,"count":876},"terraform",68,{"key":831,"label":832,"slug":831,"count":878},67,{"key":880,"label":62,"slug":880,"count":881},"java",64,{"key":883,"label":884,"slug":883,"count":885},"ms-azure","MS Azure",55,{"key":887,"label":465,"slug":887,"count":888},"kubernetes",51,{"key":890,"label":77,"slug":890,"count":891},"git",50,{"key":893,"label":127,"slug":893,"count":894},"docker",47,{"key":896,"label":72,"slug":896,"count":897},"jenkins",45,{"key":899,"label":900,"slug":899,"count":805},"ms-powerbi","MS PowerBI",{"key":902,"label":903,"slug":902,"count":759},"gcp","Gcp",{"key":905,"label":906,"slug":905,"count":816},"powershell","Powershell",{"key":908,"label":909,"slug":908,"count":816},"jira","Jira",{"key":911,"label":609,"slug":911,"count":819},"ms-excel",{"key":913,"label":464,"slug":913,"count":914},"snowflake",24,{"key":916,"label":917,"slug":916,"count":914},"ansible","Ansible",{"key":919,"label":276,"slug":919,"count":914},"tableau",{"key":921,"label":922,"slug":921,"count":914},"vba","Vba",{"key":924,"label":197,"slug":924,"count":833},"linux",{"key":926,"label":927,"slug":926,"count":833},"c","C#",{"key":929,"label":930,"slug":929,"count":833},"datadog","Datadog",{"key":932,"label":429,"slug":932,"count":833},"databricks",[934,936,938,941],{"key":52,"label":52,"count":935},208,{"key":334,"label":334,"count":937},53,{"key":939,"label":939,"count":940},"EUR",9,{"key":424,"label":424,"count":942},5,[944,945],{"key":55,"label":55,"count":34},{"key":946,"label":946,"count":94},"PART_TIME",{"total":948,"jobs":949},0,[]]