[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"job-search-\u002Fen-in\u002Fjobs-by-skill\u002Fsql?page=2":3,"seo-content-skill-sql-in":707,"skill-page-filters-\u002Fen-in\u002Fjobs-by-skill\u002Fsql?page=2":737,"featured-jobs-\u002Fen-in\u002Fjobs-by-skill\u002Fsql?page=2":932},{"total":4,"jobs":5},229,[6,64,107,132,199,226,261,287,317,337,371,394,469,510,546,568,599,613,638,654],{"id":7,"slug":8,"title":9,"raw_title":10,"is_featured":11,"company":12,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":15,"processed_country_iso_code_gmaps":17,"processed_home_office":19,"processed_salary_min":20,"processed_salary_max":21,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":24,"processed_employment_types":26,"processed_it_skills":27,"processed_it_skills_labels":31,"processed_job_expertise_skills":46,"processed_job_expertise_skills_labels":47,"max_cpc":63,"actual_cpc":63},84440,"team-lead-gre-operations-invesco-india-private-limited-sez-unit","Team Lead - GRE Operations",null,false,{"name":13,"slug":14,"logo_url":10},"Invesco (India) Private Limited - SEZ Unit","invesco-india-private-limited-sez-unit",[16],"Hyderabad",[18],"IN","hybrid",3000000,5000000,"INR","estimated",[25],"FULL_TIME","permanent",{"r":28,"etl":28,"gis":28,"sql":29,"apis":28,"excel":30,"pandas":28,"python":29,"alteryx":28,"tableau":28,"power bi":29,"powerpoint":29,"power query":28,"machine learning":28},2,3,4,[32,33,34,35,36,37,38,39,40,41,42,43,44,45],"Power BI","Python","SQL","Excel","PowerPoint","GIS","Tableau","R","Machine Learning","Alteryx","Power Query","Pandas","APIs","ETL",{"compliance":30,"forecasting":30,"econometrics":30,"data analytics":30,"data governance":30,"data management":30,"client reporting":30,"process improvement":30,"strategic analytics":30,"real estate research":30,"statistical modelling":30,"operational excellence":30,"gis & spatial analytics":30,"marketing presentations":30,"risk & escalation management":30},[48,49,50,51,52,53,54,55,56,57,58,59,60,61,62],"Strategic Analytics","Real Estate Research","Data Analytics","Forecasting","Marketing Presentations","Compliance","Statistical Modelling","Econometrics","Data Management","Data Governance","GIS & Spatial Analytics","Client Reporting","Operational Excellence","Process Improvement","Risk & Escalation Management",1,{"id":65,"slug":66,"title":67,"raw_title":10,"is_featured":11,"company":68,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":71,"processed_country_iso_code_gmaps":73,"processed_home_office":19,"processed_salary_min":74,"processed_salary_max":20,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":75,"processed_employment_types":26,"processed_it_skills":76,"processed_it_skills_labels":77,"processed_job_expertise_skills":97,"processed_job_expertise_skills_labels":98,"max_cpc":63,"actual_cpc":63},80131,"full-stack-developer-consultantsenior-consultant-allstate-india-pvt-ltd","Full Stack Developer Consultant\u002FSenior Consultant",{"name":69,"slug":70,"logo_url":10},"Allstate India Pvt Ltd","allstate-india-pvt-ltd",[72],"Pune",[18],1500000,[25],{"git":30,"npm":29,"sql":30,"tdd":30,"java":30,"saml":29,"kafka":29,"maven":29,"oauth":29,"owasp":29,"gradle":29,"openid":29,"python":28,"jenkins":29,"react.js":30,"rest apis":30,"artifactory":29,"spring boot":30,"microservices":30,"microsoft fabric":28,"observability tools":28},[78,79,80,34,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,33],"Java","Spring Boot","React.js","TDD","Microsoft Fabric","Kafka","Observability tools","REST APIs","Microservices","OAuth","OWASP","OpenID","SAML","Git","Maven","Gradle","npm","Artifactory","Jenkins",{"ci\u002Fcd":30,"api security":29,"database design":29,"agile methodologies":30,"distributed systems":30,"software architecture":30,"full stack development":30,"performance optimization":29},[99,100,101,102,103,104,105,106],"Full Stack Development","Software Architecture","Distributed Systems","API Security","Agile Methodologies","CI\u002FCD","Performance Optimization","Database Design",{"id":108,"slug":109,"title":110,"raw_title":10,"is_featured":11,"company":111,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":112,"processed_country_iso_code_gmaps":113,"processed_home_office":19,"processed_salary_min":114,"processed_salary_max":115,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":116,"processed_employment_types":26,"processed_it_skills":117,"processed_it_skills_labels":118,"processed_job_expertise_skills":120,"processed_job_expertise_skills_labels":121,"max_cpc":63,"actual_cpc":63},84427,"analyst-proxy-voting-invesco-india-private-limited-sez-unit","Analyst - Proxy Voting",{"name":13,"slug":14,"logo_url":10},[16],[18],800000,1200000,[25],{"sql":29,"excel":29,"python":29,"data visualization software":29},[34,35,33,119],"Data Visualization Software",{"automation":28,"proxy voting":29,"data analysis":29,"reconciliation":28,"capital markets":28,"asset management":28,"process improvement":28,"corporate governance":28,"operational controls":28,"regulatory reporting":28,"investment stewardship":28},[122,123,124,125,126,61,127,128,129,130,131],"Proxy Voting","Corporate Governance","Investment Stewardship","Regulatory Reporting","Operational Controls","Automation","Reconciliation","Data Analysis","Capital Markets","Asset Management",{"id":133,"slug":134,"title":135,"raw_title":10,"is_featured":11,"company":136,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":139,"processed_country_iso_code_gmaps":140,"processed_home_office":19,"processed_salary_min":21,"processed_salary_max":141,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":142,"processed_employment_types":26,"processed_it_skills":143,"processed_it_skills_labels":144,"processed_job_expertise_skills":178,"processed_job_expertise_skills_labels":179,"max_cpc":63,"actual_cpc":63},83074,"data-science-and-ai-engineering-lead-vp-f337-deutsche-india-private-limited-pune-branch","Data Science and AI Engineering Lead​, VP",{"name":137,"slug":138,"logo_url":10},"F337 Deutsche India Private Limited, Pune Branch","f337-deutsche-india-private-limited-pune-branch",[72],[18],8000000,[25],{"adk":30,"gke":30,"sql":29,"java":29,"flask":30,"neo4j":30,"redis":30,"spark":30,"denodo":30,"github":30,"looker":30,"mlflow":30,"python":30,"fastapi":30,"fastmcp":30,"mongodb":30,"pytorch":30,"vs code":30,"bigquery":30,"cloudsql":30,"pinecone":30,"langchain":30,"langgraph":30,"snowflake":30,"databricks":30,"postgresql":30,"tensorflow":30,"claude code":30,"gcp cloudrun":30,"hugging face":30,"scikit-learn":30,"cloud composer":30,"github copilot":30,"google vertexai":30,"jupyter notebook":30,"weights and biases":30},[33,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,34,78,176,177],"FastAPI","Flask","FastMcp","LangGraph","ADK","Google VertexAI","GitHub","VS Code","PyTorch","TensorFlow","scikit-learn","MLflow","Weights and Biases","Jupyter Notebook","Hugging Face","Langchain","Neo4J","GCP CloudRun","GKE","BigQuery","Cloud Composer","CloudSQL","Looker","PostgreSQL","Pinecone","Spark","MongoDB","Redis","Databricks","Denodo","Snowflake","Claude Code","GitHub Copilot",{"deployment":30,"roi analysis":29,"ai governance":30,"api architecture":30,"data engineering":30,"budget management":29,"people management":30,"ai risk management":30,"feature engineering":30,"ai model integration":30,"ai model optimization":30,"data product creation":30,"performance monitoring":30,"testing and validation":30,"research and innovation":30,"ai solution architecture":30,"cross-functional collaboration":30,"cloud infrastructure management":30,"software development lifecycle (sdlc)":30},[180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198],"AI Solution Architecture","AI Model Integration","AI Model Optimization","API Architecture","Cloud Infrastructure Management","AI Governance","AI Risk Management","Software Development Lifecycle (SDLC)","Data Engineering","Feature Engineering","Data Product Creation","Performance Monitoring","Testing and Validation","Deployment","Research and Innovation","Cross-Functional Collaboration","People Management","Budget Management","ROI Analysis",{"id":200,"slug":201,"title":202,"raw_title":10,"is_featured":11,"company":203,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":206,"processed_country_iso_code_gmaps":208,"processed_home_office":19,"processed_salary_min":74,"processed_salary_max":209,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":210,"processed_employment_types":26,"processed_it_skills":211,"processed_it_skills_labels":212,"processed_job_expertise_skills":218,"processed_job_expertise_skills_labels":219,"max_cpc":63,"actual_cpc":63},82784,"workday-prism-analytics-and-reporting-consultant-hr-it-associate-f335-deutsche-india-private-limited-bangalore-branch","Workday Prism Analytics and Reporting Consultant – HR IT, Associate",{"name":204,"slug":205,"logo_url":10},"F335 Deutsche India Private Limited, Bangalore Branch","f335-deutsche-india-private-limited-bangalore-branch",[207],"Bangalore",[18],2500000,[25],{"etl":29,"sql":28,"ai tools":29,"workday hcm":29,"workday reporting":30,"data visualization":29,"workday prism analytics":30},[213,214,215,45,216,34,217],"Workday Prism Analytics","Workday Reporting","Workday HCM","Data Visualization","AI Tools",{"compliance":29,"data modeling":30,"data governance":29,"access management":29,"process improvement":29,"data pipeline design":30,"hr data transformation":30,"security configuration":29,"technical documentation":29},[220,221,222,57,53,61,223,224,225],"HR Data Transformation","Data Pipeline Design","Data Modeling","Technical Documentation","Security Configuration","Access Management",{"id":227,"slug":228,"title":229,"raw_title":10,"is_featured":11,"company":230,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":234,"processed_country_iso_code_gmaps":236,"processed_home_office":19,"processed_salary_min":237,"processed_salary_max":238,"processed_salary_currency":239,"processed_salary_source":23,"processed_working_hours":240,"processed_employment_types":26,"processed_it_skills":242,"processed_it_skills_labels":243,"processed_job_expertise_skills":253,"processed_job_expertise_skills_labels":254,"max_cpc":63,"actual_cpc":63},81803,"ai-automation-specialist2881-allianz-insurance","AI Automation Specialist_2881",{"name":231,"slug":232,"logo_url":233},"Allianz Insurance","allianz-insurance","https:\u002F\u002Fcdn.phenompeople.com\u002FCareerConnectResources\u002FAISAIPGB\u002Fimages\u002FHeader-1706868786965.svg",[72,235],"Trivandrum",[18],70000,100000,"EUR",[25,241],"PART_TIME",{"sql":29,"faiss":29,"numpy":29,"crewai":30,"pandas":29,"python":30,"autogen":30,"grafana":28,"chromadb":29,"pinecone":29,"power bi":28,"rest api":30,"weaviate":29,"langchain":30,"langgraph":30},[33,34,244,148,245,246,247,169,248,249,250,43,251,252,32],"LangChain","AutoGen","CrewAI","REST API","Weaviate","FAISS","ChromaDB","NumPy","Grafana",{"ci\u002Fcd":29,"devsecops":29,"rag pipelines":30,"data analytics":29,"llm integration":30,"agentic ai development":30,"ai security & guardrails":30,"cybersecurity domain awareness":29},[255,256,257,258,50,259,260,104],"Agentic AI Development","LLM Integration","RAG Pipelines","AI Security & Guardrails","Cybersecurity Domain Awareness","DevSecOps",{"id":262,"slug":263,"title":264,"raw_title":10,"is_featured":11,"company":265,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":268,"processed_country_iso_code_gmaps":270,"processed_home_office":271,"processed_salary_min":20,"processed_salary_max":21,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":272,"processed_employment_types":26,"processed_it_skills":273,"processed_it_skills_labels":274,"processed_job_expertise_skills":275,"processed_job_expertise_skills_labels":276,"max_cpc":63,"actual_cpc":63},85645,"fixed-income-division-senior-associate-manager-desk-strategist-etf-primary-and-secondary-trading-workflow-mumbai-morgan-stanley-advantage-svcs","Fixed Income Division - Senior Associate\u002F Manager, Desk Strategist – ETF Primary and Secondary Trading Workflow (Mumbai)",{"name":266,"slug":267,"logo_url":10},"Morgan Stanley Advantage Svcs","morgan-stanley-advantage-svcs",[269],"Mumbai",[18],"onsite",[25],{"sql":29,"python":29,"data visualization":29},[33,34,216],{"valuation":30,"statistics":29,"etf business":30,"fixed income":30,"data analytics":30,"risk management":30,"business analysis":30,"functional design":30,"derivative pricing":30,"quantitative analysis":30,"stakeholder management":30},[277,278,279,280,281,282,283,50,284,285,286],"Fixed Income","ETF Business","Derivative Pricing","Quantitative Analysis","Business Analysis","Risk Management","Valuation","Stakeholder Management","Functional Design","Statistics",{"id":288,"slug":289,"title":290,"raw_title":10,"is_featured":11,"company":291,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":292,"processed_country_iso_code_gmaps":293,"processed_home_office":19,"processed_salary_min":294,"processed_salary_max":295,"processed_salary_currency":239,"processed_salary_source":23,"processed_working_hours":296,"processed_employment_types":26,"processed_it_skills":297,"processed_it_skills_labels":298,"processed_job_expertise_skills":307,"processed_job_expertise_skills_labels":308,"max_cpc":63,"actual_cpc":63},81730,"data-engineer3333-allianz-insurance","Data Engineer_3333",{"name":231,"slug":232,"logo_url":233},[72],[18],80000,120000,[25],{"git":29,"sql":30,"ci\u002Fcd":29,"spark":30,"devops":29,"mlflow":29,"python":30,"pyspark":30,"spark sql":30,"databricks":30,"delta lake":30,"unity catalog":30,"databricks workflows":30,"azure synapse analytics":30,"databricks asset bundles":30},[173,170,299,156,300,301,302,303,304,305,34,33,91,104,306],"Delta Lake","Azure Synapse Analytics","PySpark","Spark SQL","Unity Catalog","Databricks Workflows","Databricks Asset Bundles","DevOps",{"mentoring":29,"data lineage":29,"data modeling":30,"data security":29,"etl migration":30,"data governance":29,"team leadership":29,"data engineering":30,"data architecture":30,"root cause analysis":29,"cloud data solutions":30,"performance optimization":30},[188,309,222,310,311,105,57,312,313,314,315,316],"Data Architecture","Cloud Data Solutions","ETL Migration","Data Lineage","Data Security","Root Cause Analysis","Team Leadership","Mentoring",{"id":318,"slug":319,"title":320,"raw_title":10,"is_featured":11,"company":321,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":322,"processed_country_iso_code_gmaps":323,"processed_home_office":19,"processed_salary_min":115,"processed_salary_max":324,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":325,"processed_employment_types":26,"processed_it_skills":326,"processed_it_skills_labels":327,"processed_job_expertise_skills":328,"processed_job_expertise_skills_labels":329,"max_cpc":63,"actual_cpc":63},84434,"risk-analyst-invesco-india-private-limited-sez-unit-2","Risk Analyst",{"name":13,"slug":14,"logo_url":10},[16],[18],1800000,[25],{"r":30,"sql":30,"python":30},[33,39,34],{"ai usage":28,"data analysis":30,"risk management":30,"asset management":29,"market risk monitoring":30,"portfolio construction":30,"performance attribution":30,"equity risk factor models":30,"liquidity risk monitoring":30,"quantitative model development":30},[282,330,331,129,332,333,334,335,131,336],"Quantitative Model Development","Portfolio Construction","Equity Risk Factor Models","Performance Attribution","Market Risk Monitoring","Liquidity Risk Monitoring","AI Usage",{"id":338,"slug":339,"title":340,"raw_title":10,"is_featured":11,"company":341,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":344,"processed_country_iso_code_gmaps":345,"processed_home_office":271,"processed_salary_min":346,"processed_salary_max":347,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":348,"processed_employment_types":26,"processed_it_skills":349,"processed_it_skills_labels":350,"processed_job_expertise_skills":357,"processed_job_expertise_skills_labels":358,"max_cpc":63,"actual_cpc":63},83022,"risk-and-trading-as-9608-deutsche-india-private-limited-mumbai-branch","Risk and Trading, AS",{"name":342,"slug":343,"logo_url":10},"9608 Deutsche India Private Limited, Mumbai Branch","9608-deutsche-india-private-limited-mumbai-branch",[269],[18],2000000,3500000,[25],{"sql":29,"itap":29,"kannon":29,"kondor":29,"python":29,"summit":29,"bloomberg":29,"dbanalytics":29},[33,34,351,352,353,354,355,356],"Bloomberg","Kondor","Summit","iTAP","Kannon","DBAnalytics",{"hedging":30,"ai tools":29,"bond pricing":30,"data analysis":30,"debt issuance":30,"trade capture":30,"risk management":30,"capital management":30,"financial modeling":30,"liquidity management":30,"fixed income products":30,"life-cycle management":30,"quantitative analysis":30,"market risk management":30,"funding curve methodologies":30,"asset and liability management":30},[359,282,360,361,362,363,364,365,366,367,368,369,370,280,129,217],"Fixed Income Products","Bond Pricing","Funding Curve Methodologies","Market Risk Management","Debt Issuance","Hedging","Trade Capture","Life-Cycle Management","Liquidity Management","Capital Management","Asset and Liability Management","Financial Modeling",{"id":372,"slug":373,"title":374,"raw_title":10,"is_featured":11,"company":375,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":376,"processed_country_iso_code_gmaps":377,"processed_home_office":19,"processed_salary_min":74,"processed_salary_max":209,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":378,"processed_employment_types":26,"processed_it_skills":379,"processed_it_skills_labels":380,"processed_job_expertise_skills":382,"processed_job_expertise_skills_labels":383,"max_cpc":63,"actual_cpc":63},84436,"sr-ba-ii-invesco-india-private-limited-sez-unit","Sr. BA II",{"name":13,"slug":14,"logo_url":10},[16],[18],[25],{"sql":30,"python":30,"microsoft office":29},[34,33,381],"Microsoft Office",{"agile":29,"data risk":29,"data analysis":30,"data modeling":29,"data lifecycle":29,"data governance":29,"asset management":30,"business analysis":30,"financial services":30,"project management":29,"process improvement":29,"business intelligence":29,"investment management":30,"master data management":29,"requirements gathering":30,"user acceptance testing":29},[281,129,384,57,222,385,386,387,388,389,131,390,391,61,392,393],"Requirements Gathering","Master Data Management","Business Intelligence","Agile","Project Management","Investment Management","Financial Services","User Acceptance Testing","Data Lifecycle","Data Risk",{"id":395,"slug":396,"title":397,"raw_title":10,"is_featured":11,"company":398,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":399,"processed_country_iso_code_gmaps":402,"processed_home_office":19,"processed_salary_min":238,"processed_salary_max":403,"processed_salary_currency":404,"processed_salary_source":23,"processed_working_hours":405,"processed_employment_types":26,"processed_it_skills":406,"processed_it_skills_labels":407,"processed_job_expertise_skills":439,"processed_job_expertise_skills_labels":440,"max_cpc":63,"actual_cpc":63},81755,"lead-consultant-java3007-allianz-insurance","Lead Consultant (Java)_3007",{"name":231,"slug":232,"logo_url":233},[400,401],"PUNE","Sindewahi",[18],150000,"AUD",[25],{"aws":30,"git":30,"jsp":30,"jwt":30,"rag":30,"sca":30,"sql":30,"uml":30,"dast":30,"j2ee":30,"java":30,"rxjs":30,"sast":30,"azure":30,"ci\u002Fcd":30,"junit":30,"nosql":30,"bamboo":30,"docker":30,"oauth2":30,"stride":30,"angular":30,"ansible":30,"jenkins":30,"selenium":30,"openshift":30,"rest apis":30,"javascript":30,"kubernetes":30,"typescript":30,"spring boot":30,"jasmine\u002Fkarma":30,"jpa\u002Fhibernate":30,"microservices":30,"vector stores":30,"github actions":30,"spring security":30,"prompt engineering":30,"owasp top 10 for llm applications":30},[78,408,79,85,86,409,410,411,412,413,414,415,34,416,417,418,419,420,421,104,96,422,91,423,424,425,426,427,428,429,430,431,432,433,434,435,436,437,438],"J2EE","Spring Security","JPA\u002FHibernate","Angular","TypeScript","RxJS","JavaScript","JSP","NoSQL","OAuth2","JWT","Prompt Engineering","RAG","Vector Stores","GitHub Actions","Bamboo","Ansible","JUnit","Selenium","Jasmine\u002FKarma","AWS","Azure","Kubernetes","OpenShift","Docker","UML","SAST","DAST","SCA","STRIDE","OWASP Top 10 for LLM Applications",{"r&d":30,"devsecops":30,"compliance":30,"estimation":30,"agile scrum":30,"it controls":30,"ai governance":30,"api management":30,"risk assessment":30,"solution design":30,"domain modelling":30,"solution reviews":30,"customer insights":30,"financial control":30,"health and safety":30,"quality assurance":30,"ai cost management":30,"licence management":30,"performance tuning":30,"talent acquisition":30,"dependency analysis":30,"software deployment":30,"ai impact measurement":30,"cyber risk management":30,"software architecture":30,"continuous improvement":30,"environment strategies":30,"full-stack development":30,"performance monitoring":30,"enterprise architecture":30,"technical documentation":30,"ai regulatory compliance":30,"vulnerability management":30,"business case development":30},[100,441,442,260,443,185,444,445,446,447,448,449,450,451,452,453,454,455,223,456,191,457,458,459,460,461,462,463,464,465,466,467,468,53],"Solution Design","Full-Stack Development","API Management","AI Cost Management","AI Regulatory Compliance","Quality Assurance","Performance Tuning","Agile Scrum","Enterprise Architecture","Domain Modelling","IT Controls","Software Deployment","Licence Management","Cyber Risk Management","Vulnerability Management","Talent Acquisition","Financial Control","Risk Assessment","Dependency Analysis","Estimation","Environment Strategies","Solution Reviews","AI Impact Measurement","Continuous Improvement","R&D","Business Case Development","Health and Safety","Customer Insights",{"id":470,"slug":471,"title":472,"raw_title":10,"is_featured":11,"company":473,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":474,"processed_country_iso_code_gmaps":475,"processed_home_office":19,"processed_salary_min":74,"processed_salary_max":209,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":476,"processed_employment_types":10,"processed_it_skills":477,"processed_it_skills_labels":478,"processed_job_expertise_skills":493,"processed_job_expertise_skills_labels":494,"max_cpc":63,"actual_cpc":63},83078,"information-security-associate-f337-deutsche-india-private-limited-pune-branch","Information Security Associate",{"name":137,"slug":138,"logo_url":10},[72],[18],[25],{"etl":28,"sql":29,"vba":28,"jira":28,"unix":28,"hp-alm":28,"python":28,"ai tools":29,"ms excel":29,"confluence":28,"powershell":28,"servicenow":28,"sharepoint":28,"microsoft azure":28,"active directory":28,"unix shell scripting":28,"google cloud platform":28,"database administration":28},[479,34,45,480,481,482,483,484,485,486,487,488,33,489,490,491,492,217],"MS Excel","Active Directory","Database Administration","Google Cloud Platform","Microsoft Azure","ServiceNow","HP-ALM","SharePoint","Confluence","Jira","VBA","Unix Shell Scripting","PowerShell","Unix",{"it audit":28,"analytics":29,"reporting":29,"data quality":29,"it governance":29,"risk and control":28,"access management":30,"big data handling":29,"it project management":28,"it service management":29,"banking\u002Ffinancial domain":28,"privileged access management":28,"information security concepts":29,"authorization and authentication":30,"identity and access management (iam)":30,"it frameworks (cobit5, itil, iso27001)":28},[495,225,496,497,498,499,500,501,502,503,504,505,506,507,508,509],"Identity and Access Management (IAM)","Authorization and Authentication","IT Governance","IT Service Management","Data Quality","Reporting","Analytics","Big Data Handling","IT Frameworks (COBIT5, ITIL, ISO27001)","Information Security Concepts","Risk and Control","IT Project Management","Privileged Access Management","IT Audit","Banking\u002FFinancial Domain",{"id":511,"slug":512,"title":513,"raw_title":10,"is_featured":11,"company":514,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":515,"processed_country_iso_code_gmaps":516,"processed_home_office":19,"processed_salary_min":20,"processed_salary_max":21,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":517,"processed_employment_types":26,"processed_it_skills":518,"processed_it_skills_labels":519,"processed_job_expertise_skills":532,"processed_job_expertise_skills_labels":533,"max_cpc":63,"actual_cpc":63},83093,"gcp-data-ai-engineer-as-f337-deutsche-india-private-limited-pune-branch","GCP Data & AI Engineer, AS",{"name":137,"slug":138,"logo_url":10},[72],[18],[25],{"aws":28,"gcp":30,"sql":30,"llms":30,"azure":28,"ci\u002Fcd":30,"docker":30,"python":30,"bigquery":30,"cloud run":30,"rest apis":30,"terraform":30,"cloud build":30,"dialogflow cx":30,"apache airflow":30,"cloud composer":30,"embedding models":30,"vector databases":30,"artifact registry":30,"gemini enterprise agent platform":30,"google agent development kit (adk)":30},[33,34,520,164,165,521,522,523,104,524,525,432,85,526,527,528,529,530,531,429,428],"GCP","Apache Airflow","Cloud Run","Terraform","Cloud Build","Artifact Registry","Dialogflow CX","Gemini Enterprise Agent Platform","Google Agent Development Kit (ADK)","Vector Databases","Embedding Models","LLMs",{"etl testing":30,"rag systems":30,"generative ai":30,"system design":30,"data engineering":30,"agentic workflows":30,"conversational ai":30,"production support":30,"ml model deployment":30,"infrastructure as code":30,"security and governance":30,"data pipeline development":30,"ai application development":30},[188,534,535,536,537,538,539,540,541,542,543,544,545],"AI Application Development","System Design","Generative AI","RAG Systems","Agentic Workflows","Conversational AI","ML Model Deployment","Data Pipeline Development","ETL Testing","Infrastructure as Code","Security and Governance","Production Support",{"id":547,"slug":548,"title":549,"raw_title":10,"is_featured":11,"company":550,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":553,"processed_country_iso_code_gmaps":554,"processed_home_office":271,"processed_salary_min":555,"processed_salary_max":556,"processed_salary_currency":557,"processed_salary_source":23,"processed_working_hours":558,"processed_employment_types":26,"processed_it_skills":559,"processed_it_skills_labels":560,"processed_job_expertise_skills":563,"processed_job_expertise_skills_labels":564,"max_cpc":63,"actual_cpc":63},88244,"associate-performance-analytics-tiaa-global-capabilities-private-limited","Associate - Performance & Analytics",{"name":551,"slug":552,"logo_url":10},"TIAA Global Capabilities Private Limited","tiaa-global-capabilities-private-limited",[269],[18],60000,90000,"USD",[25],{"r":29,"sql":29,"excel":29,"python":29,"tableau":29,"power bi":29,"statistical software":29,"data visualization tools":29},[33,34,39,38,32,35,561,562],"Data Visualization Tools","Statistical Software",{"statistics":30,"data mining":30,"data analytics":30,"data engineering":29,"project management":29,"predictive modeling":30,"statistical modeling":30,"business intelligence":30},[50,565,566,567,188,386,286,388],"Statistical Modeling","Predictive Modeling","Data Mining",{"id":569,"slug":570,"title":571,"raw_title":10,"is_featured":11,"company":572,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":575,"processed_country_iso_code_gmaps":576,"processed_home_office":271,"processed_salary_min":209,"processed_salary_max":577,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":578,"processed_employment_types":26,"processed_it_skills":579,"processed_it_skills_labels":580,"processed_job_expertise_skills":589,"processed_job_expertise_skills_labels":590,"max_cpc":63,"actual_cpc":63},88193,"senior-software-engineerjava-hartford-global-services-private-limited","Senior Software Engineer\u002FJava",{"name":573,"slug":574,"logo_url":10},"Hartford Global Services Private Limited","hartford-global-services-private-limited",[16],[18],4000000,[25],{"aws":30,"git":29,"jms":29,"sql":29,"java":30,"rest":29,"soap":29,"rally":28,"github":29,"ibm mq":29,"python":29,"angular":29,"jenkins":29,"sonarqube":28,"terraform":29,"spring batch":28,"generative ai":28,"cloudformation":29,"google cloud platform":28},[78,411,428,33,34,523,581,582,583,151,96,584,585,586,587,91,536,482,588],"CloudFormation","JMS","IBM MQ","Rally","SonarQube","SOAP","REST","Spring Batch",{"ci\u002Fcd":30,"devops":30,"monitoring":29,"cloud migration":30,"hybrid integrations":30,"infrastructure as code":30,"security implementation":29,"guidewire insurancesuite":28,"web services development":29,"messaging and integration":30,"resiliency implementation":29},[591,592,543,104,306,593,594,595,596,597,598],"Cloud Migration","Messaging and Integration","Security Implementation","Resiliency Implementation","Monitoring","Hybrid Integrations","Web Services Development","Guidewire InsuranceSuite",{"id":600,"slug":601,"title":513,"raw_title":10,"is_featured":11,"company":602,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":603,"processed_country_iso_code_gmaps":604,"processed_home_office":19,"processed_salary_min":20,"processed_salary_max":21,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":605,"processed_employment_types":26,"processed_it_skills":606,"processed_it_skills_labels":607,"processed_job_expertise_skills":608,"processed_job_expertise_skills_labels":609,"max_cpc":63,"actual_cpc":63},83095,"gcp-data-ai-engineer-as-f337-deutsche-india-private-limited-pune-branch-2",{"name":137,"slug":138,"logo_url":10},[72],[18],[25],{"aws":29,"gcp":30,"sql":30,"llms":30,"azure":29,"ci\u002Fcd":30,"docker":30,"python":30,"bigquery":30,"cloud run":30,"rest apis":30,"terraform":30,"cloud build":30,"dialogflow cx":30,"apache airflow":30,"cloud composer":30,"embedding models":30,"vector databases":30,"artifact registry":30,"gemini enterprise agent platform":30,"google agent development kit (adk)":30},[33,34,520,164,165,521,522,523,104,524,525,432,85,526,527,528,529,530,531,429,428],{"agentops":30,"system design":30,"data engineering":30,"conversational ai":30,"production support":30,"generative ai systems":30,"infrastructure as code":30,"security and governance":30,"ai application development":30,"agentic ai application development":30},[188,534,535,539,610,611,612,543,544,545],"Generative AI Systems","Agentic AI Application Development","AgentOps",{"id":614,"slug":615,"title":616,"raw_title":10,"is_featured":11,"company":617,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":620,"processed_country_iso_code_gmaps":621,"processed_home_office":271,"processed_salary_min":295,"processed_salary_max":622,"processed_salary_currency":557,"processed_salary_source":23,"processed_working_hours":623,"processed_employment_types":26,"processed_it_skills":624,"processed_it_skills_labels":625,"processed_job_expertise_skills":630,"processed_job_expertise_skills_labels":631,"max_cpc":63,"actual_cpc":63},80752,"associate-director-technical-business-analyst-apollo-india-services-llp","Associate Director - Technical Business Analyst",{"name":618,"slug":619,"logo_url":10},"Apollo India Services LLP","apollo-india-services-llp",[269],[18],180000,[25],{"sql":29,"vb.net":29,"hyperion":29,"ms excel":30,"onestream":30,"ms powerpoint":30},[626,627,628,34,479,629],"OneStream","Hyperion","VB.net","MS PowerPoint",{"training":30,"sox compliance":30,"business analysis":30,"production support":30,"sdlc methodologies":30,"financial reporting":30,"system enhancements":30,"technical documentation":30,"entitlements provisioning":30},[632,281,223,633,634,635,636,545,637],"Financial Reporting","SOX Compliance","SDLC Methodologies","Entitlements Provisioning","System Enhancements","Training",{"id":639,"slug":640,"title":641,"raw_title":10,"is_featured":11,"company":642,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":643,"processed_country_iso_code_gmaps":644,"processed_home_office":19,"processed_salary_min":20,"processed_salary_max":21,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":645,"processed_employment_types":26,"processed_it_skills":646,"processed_it_skills_labels":647,"processed_job_expertise_skills":650,"processed_job_expertise_skills_labels":651,"max_cpc":63,"actual_cpc":63},83098,"gcp-data-and-ai-engineer-avp-f337-deutsche-india-private-limited-pune-branch","GCP Data and AI Engineer, AVP",{"name":137,"slug":138,"logo_url":10},[72],[18],[25],{"aws":29,"gcp":30,"sql":30,"azure":29,"ci\u002Fcd":30,"docker":30,"python":30,"pub\u002Fsub":30,"bigquery":30,"cloud run":30,"rest apis":30,"terraform":30,"vertex ai":30,"cloud build":30,"dialogflow cx":30,"apache airflow":30,"cloud composer":30,"artifact registry":30,"gemini enterprise agent platform":30,"google agent development kit (adk)":30},[33,34,520,164,165,521,522,523,104,524,525,432,85,648,526,527,528,649,429,428],"Vertex AI","Pub\u002FSub",{"llms":30,"agentops":30,"etl testing":30,"rag systems":30,"data modeling":30,"generative ai":30,"system design":30,"data engineering":30,"embedding models":30,"vector databases":30,"agentic workflows":30,"conversational ai":30,"query optimization":30,"distributed systems":30,"multi-agent systems":30,"infrastructure as code":30,"security and governance":30,"ai application development":30},[188,534,536,537,538,535,101,222,652,543,544,542,539,531,529,530,653,612],"Query Optimization","Multi-agent Systems",{"id":655,"slug":656,"title":657,"raw_title":10,"is_featured":11,"company":658,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":659,"processed_country_iso_code_gmaps":660,"processed_home_office":19,"processed_salary_min":346,"processed_salary_max":347,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":661,"processed_employment_types":26,"processed_it_skills":662,"processed_it_skills_labels":663,"processed_job_expertise_skills":689,"processed_job_expertise_skills_labels":690,"max_cpc":63,"actual_cpc":706},83099,"gcp-full-stack-data-ai-engineer-as-f337-deutsche-india-private-limited-pune-branch","GCP Full-Stack Data & AI Engineer, AS",{"name":137,"slug":138,"logo_url":10},[72],[18],[25],{"git":30,"iam":30,"jwt":30,"sql":30,"cors":30,"ci\u002Fcd":30,"flask":30,"owasp":30,"react":30,"docker":30,"pytest":30,"python":30,"angular":30,"fastapi":30,"postman":30,"pub\u002Fsub":29,"bigquery":30,"cloud run":30,"cloud sql":29,"firestore":29,"oauth 2.0":30,"rest apis":30,"terraform":30,"embeddings":30,"guardrails":29,"javascript":30,"typescript":30,"cloud build":30,"memorystore":29,"api gateways":30,"cloud storage":30,"dialogflow cx":30,"gemini models":30,"rate limiting":30,"apache airflow":29,"cloud composer":29,"openid connect":30,"secret manager":30,"cx agent studio":30,"human oversight":29,"input validation":30,"vector databases":30,"artifact registry":30,"secrets management":30,"google cloud platform":30,"google cloud operations":30,"agent-to-agent protocols":29,"multi-agent orchestration":29,"google agent development kit (adk)":30},[33,34,414,412,664,411,145,146,85,482,522,164,665,666,165,521,649,667,668,669,91,432,523,525,524,104,670,671,418,672,673,674,675,676,677,88,678,679,680,681,682,683,526,684,528,685,686,687,688],"React","Cloud Storage","Secret Manager","Cloud SQL","Firestore","Memorystore","OAuth 2.0","OpenID Connect","IAM","API gateways","CORS","rate limiting","secrets management","input validation","Postman","Pytest","Google Cloud Operations","Gemini models","embeddings","vector databases","CX Agent Studio","multi-agent orchestration","agent-to-agent protocols","guardrails","human oversight",{"devops":30,"agentic ai":30,"data lineage":30,"data quality":30,"generative ai":30,"orchestration":30,"ai engineering":30,"data modelling":30,"responsible ai":30,"data governance":30,"data engineering":30,"capacity planning":30,"incident response":30,"secure publishing":30,"cloud architecture":30,"query optimization":30,"architecture design":30,"quality engineering":30,"security engineering":30,"software engineering":30,"full-stack development":30,"technical documentation":30,"operations & reliability":30,"batch and streaming design":30},[691,442,188,692,693,306,694,695,696,536,697,223,698,699,700,701,702,703,499,312,57,652,704,705],"Software Engineering","AI Engineering","Cloud Architecture","Quality Engineering","Security Engineering","Operations & Reliability","Agentic AI","Architecture Design","Incident Response","Capacity Planning","Data Modelling","Batch and Streaming Design","Orchestration","Secure Publishing","Responsible AI",0.3,{"image_path":708,"content_de":709,"content_en":722,"composite_key":735,"last_updated":736},"\u002Fimages\u002Fskill\u002Fsql.webp",{"tab1":710,"tab2":713,"tab3":716,"tab4":719},{"title":711,"content":712},"Bedeutung & Relevanz","SQL (Structured Query Language) spielt eine entscheidende Rolle in der indischen Finanzbranche, da es die Grundlage für effizientes Datenmanagement und -analyse bildet. In einem Land mit einem schnell wachsenden Finanzsektor wie [Indien](\u002Fsearch) ermöglicht SQL die Verarbeitung großer Datenmengen, die für [Finanzanalyse](\u002Fjobs-by-expertise\u002Ffinancial-analysis), [Risikomanagement](\u002Fjobs-by-expertise\u002Frisk-management) und [Portfoliomanagement](\u002Fjobs-by-expertise\u002Fportfolio-management) unerlässlich sind. Unternehmen nutzen SQL, um Finanzdatenbanken zu verwalten, Transaktionen zu überwachen und Berichte für Compliance-Zwecke zu generieren. Die Fähigkeit, komplexe Abfragen zu erstellen, ist besonders wertvoll für die Integration von Marktdaten aus Plattformen wie Bloomberg und Refinitiv, die in der indischen Finanzwelt weit verbreitet sind. Mit der zunehmenden Digitalisierung gewinnt SQL an Bedeutung, um datengesteuerte Entscheidungen in Bereichen wie [Asset Management](\u002Fjobs-by-industry\u002Fasset-management) und [Banking](\u002Fjobs-by-industry\u002Fbanking) zu unterstützen. Es fördert die Effizienz durch Automatisierung von Prozessen wie Datenvalidierung und Berichterstattung, was in einem wettbewerbsintensiven Markt wie Indien einen strategischen Vorteil bietet.",{"title":714,"content":715},"Top-Branchen & Standorte","In [Indien](\u002Fsearch) ist SQL in mehreren Schlüsselbranchen hochgefragt, darunter [Finanzdienstleistungen](\u002Fjobs-by-industry\u002Ffinancial-services), [Versicherungen](\u002Fjobs-by-industry\u002Finsurance) und [Asset Management](\u002Fjobs-by-industry\u002Fasset-management). Besonders in Städten wie Bengaluru, Pune und Mumbai, die als IT- und Finanzzentren gelten, wird SQL für Aufgaben wie Datenintegration, Client Reporting und Systemmigration eingesetzt. In Bengaluru, bekannt für seine Tech-Startups, nutzen Unternehmen SQL für [Finanzmodellierung](\u002Fjobs-by-expertise\u002Ffinancial-modeling) und die Verwaltung von [Finanzmärkten](\u002Fjobs-by-expertise\u002Ffinancial-markets). Pune hingegen konzentriert sich auf [Prozessverbesserung](\u002Fjobs-by-expertise\u002Fprocess-improvement) in der Finanzbranche, wobei SQL zur Optimierung von Datenworkflows beiträgt. Mumbai, das Finanzkapital Indiens, setzt SQL intensiv in [Banking](\u002Fjobs-by-industry\u002Fbanking) und [Vermögensverwaltung](\u002Fjobs-by-industry\u002Fasset-management) ein, um Investmentdaten zu analysieren und regulatorische Anforderungen zu erfüllen. Diese Standorte bieten zahlreiche Möglichkeiten für Fachkräfte, die SQL in dynamischen Umgebungen anwenden möchten.",{"title":717,"content":718},"Gefragte Skills & Arbeitgeber","Führende Unternehmen in [Indien](\u002Fsearch) wie Apex Fund Services LLP, Allianz Insurance und CO_ANT-MUM Annet Technologies Mumbai LLP suchen nach SQL-Experten, um Schlüsselexpertisen wie Fund Administration, Application Support und Data Integration zu unterstützen. SQL wird hier für [Projektmanagement](\u002Fjobs-by-expertise\u002Fproject-management), Data Validation und die Verwaltung von Financial Instruments eingesetzt. Beispielsweise nutzt Apex Fund Services LLP SQL für NAV\u002FGAV-Berechnungen und Fund Reconciliation, während Allianz Insurance es für Risk Assessment und Compliance Monitoring in Versicherungsprodukten verwendet. Zusätzlich sind Kenntnisse in Agile Methodologies und Business Requirements Analysis gefragt, um SQL-basierte Lösungen in Systemen wie Geneva und Investran zu implementieren. Diese Arbeitgeber schätzen SQL-Fähigkeiten für die Automatisierung von Prozessen wie Fee Calculations und Break Resolution, was die Effizienz in der indischen Finanzlandschaft steigert.",{"title":720,"content":721},"Karriere & Entwicklung","Karrierewege mit SQL in [Indien](\u002Fsearch) reichen von Data Analysts bis zu IT-Spezialisten in der Finanzbranche. Um SQL zu erlernen, empfehlen sich Online-Kurse, praktische Projekte mit Tools wie [MS Excel](\u002Fjobs-by-skill\u002Fms-excel) und [Python](\u002Fjobs-by-skill\u002Fpython) sowie Zertifizierungen in Datenbankmanagement. Verwandte IT-Skills wie ETL Tools, REST API und Cloud-Konfiguration mit AWS oder Azure ergänzen SQL-Kenntnisse und eröffnen Rollen in Data Analytics oder DevOps. In Indien können Fachkräfte SQL mit [Generative AI](\u002Fjobs-by-skill\u002Fgenerative-ai) kombinieren, um fortschrittliche Datenlösungen zu entwickeln, z.B. für [Prozessverbesserung](\u002Fjobs-by-expertise\u002Fprocess-improvement) oder System Integration. Typische Entwicklungsmöglichkeiten umfassen den Aufstieg zum Senior Data Engineer oder Project Manager, wobei Erfahrung in Agile Methodology und Tools wie Jira hilfreich ist. Durch kontinuierliches Lernen und Anwendung in realen Szenarien, wie Data Migration oder Financial Modeling, können Berufstätige in Indien ihre Karriere vorantreiben und von der hohen Nachfrage nach SQL-Experten profitieren.",{"tab1":723,"tab2":726,"tab3":729,"tab4":732},{"title":724,"content":725},"Strategic Importance","SQL (Structured Query Language) holds immense strategic importance in India's rapidly growing financial sector, serving as the backbone for data management, analysis, and decision-making processes. In a country where financial institutions handle massive volumes of transactional data daily, SQL enables efficient querying, manipulation, and extraction of critical information from complex databases. This skill is particularly crucial for roles involving [Financial Analysis](\u002Fjobs-by-expertise\u002Ffinancial-analysis), [Risk Management](\u002Fjobs-by-expertise\u002Frisk-management), and [Portfolio Management](\u002Fjobs-by-expertise\u002Fportfolio-management), where accurate data retrieval directly impacts investment strategies and regulatory compliance.\n\nWith India's financial services industry embracing digital transformation, SQL proficiency allows professionals to integrate data from multiple sources, perform [Data Validation](\u002Fjobs-by-expertise\u002Fdata-validation), and support [Process Automation](\u002Fjobs-by-expertise\u002Fprocess-improvement) initiatives. The ability to write optimized SQL queries is essential for generating client reports, calculating NAV\u002FGAV for funds, and managing [Financial Markets](\u002Fjobs-by-expertise\u002Ffinancial-markets) data. As Indian companies increasingly adopt cloud-based solutions and advanced analytics, SQL remains a foundational skill that bridges traditional database management with modern [Data Analytics](\u002Fjobs-by-expertise\u002Fdata-analytics) requirements.",{"title":727,"content":728},"Top Industries & Locations","SQL expertise is in high demand across India's key financial hubs and specialized sectors. In major metropolitan centers like Bengaluru, Pune, and Mumbai, financial institutions actively seek SQL professionals to support their expanding operations. These cities host numerous [Banking](\u002Fjobs-by-industry\u002Fbanking) institutions, [Asset Management](\u002Fjobs-by-industry\u002Fasset-management) firms, and insurance companies that rely heavily on database management systems.\n\nThe [Financial Services](\u002Fjobs-by-industry\u002Ffinancial-services) sector, particularly fund administration and insurance services, represents the primary demand driver for SQL skills in India. Companies specializing in [Fund Administration](\u002Fjobs-by-industry\u002Ffund-administration) require SQL for managing investment data, performing reconciliations, and supporting [Financial Modeling](\u002Fjobs-by-expertise\u002Ffinancial-modeling) activities. The insurance industry utilizes SQL for policy administration, claims processing, and risk assessment. Additionally, the growing [Private Equity](\u002Fjobs-by-industry\u002Fprivate-equity) and real estate investment sectors in India depend on SQL for portfolio tracking, performance analysis, and regulatory reporting requirements.",{"title":730,"content":731},"In-Demand Skills & Employers","Leading financial institutions in India consistently seek professionals with SQL expertise combined with complementary technical and domain knowledge. Top employers like Apex Fund Services LLP, Allianz Insurance, and CO_ANT-MUM Annet Technologies Mumbai LLP require SQL specialists for roles involving [Data Integration](\u002Fjobs-by-expertise\u002Fdata-integration), [Client Reporting](\u002Fjobs-by-expertise\u002Fclient-reporting), and [System Migration](\u002Fjobs-by-expertise\u002Fsystem-migration).\n\nThese companies value SQL professionals who can demonstrate proficiency in [Financial Data Analysis](\u002Fjobs-by-expertise\u002Ffinancial-analysis), understand [Financial Instruments](\u002Fjobs-by-expertise\u002Ffinancial-instruments), and support [Process Improvement](\u002Fjobs-by-expertise\u002Fprocess-improvement) initiatives. The most sought-after expertise includes [Reference Data Management](\u002Fjobs-by-expertise\u002Freference-data-management), [Corporate Actions](\u002Fjobs-by-expertise\u002Fcorporate-actions) processing, and [Fund Reconciliation](\u002Fjobs-by-expertise\u002Ffund-reconciliation). SQL is particularly valuable when combined with knowledge of specialized financial systems like Geneva, Investran, and various [Accounting Systems](\u002Fjobs-by-industry\u002Faccounting). Professionals who can leverage SQL for [Automated Matching](\u002Fjobs-by-expertise\u002Fautomation-solutions) and [Exception Handling](\u002Fjobs-by-expertise\u002Fexception-handling) in financial operations are especially prized in the Indian market.",{"title":733,"content":734},"Career & Development","SQL opens diverse career pathways in India's financial technology landscape, ranging from database administration to advanced analytics roles. Entry-level professionals typically start as SQL Developers or Data Analysts, progressing to roles like Database Architect, Business Intelligence Analyst, or [Financial Modeling](\u002Fjobs-by-expertise\u002Ffinancial-modeling) Specialist. The skill serves as a foundation for transitioning into [Data Analytics](\u002Fjobs-by-expertise\u002Fdata-analytics), [Risk Assessment](\u002Fjobs-by-expertise\u002Frisk-assessment), and [Project Management](\u002Fjobs-by-expertise\u002Fproject-management) positions.\n\nTo enhance SQL capabilities, professionals should complement their skills with [Python](\u002Fjobs-by-skill\u002Fpython) for advanced data manipulation, [MS Excel](\u002Fjobs-by-skill\u002Fms-excel) for reporting, and ETL tools for data integration. Learning database management systems like Microsoft SQL Server and understanding [Agile Methodologies](\u002Fjobs-by-expertise\u002Fagile-methodologies) for development processes significantly boosts career prospects. Indian professionals can benefit from mastering [Data Visualization](\u002Fjobs-by-expertise\u002Fdata-visualization) tools like Power BI alongside SQL to create comprehensive business intelligence solutions. Continuous learning in areas like [Cloud Configuration](\u002Fjobs-by-skill\u002Fcloud-configuration) and [API Development](\u002Fjobs-by-skill\u002Fapi-development) ensures SQL remains relevant in India's evolving digital financial ecosystem, while certifications in database management and financial systems provide competitive advantages in the job market.","skill:sql:in","2026-08-17T09:01:39.116970+02:00",{"industry":738,"employment_type":780,"expertise_skills":784,"it_skills":851,"salary_currency":920,"processed_working_hours":929},[739,742,746,750,754,758,761,765,768,771,774,777],{"key":740,"label":390,"count":741},"financial services",111,{"key":743,"label":744,"count":745},"financial markets infrastructure","Financial Markets Infrastructure",63,{"key":747,"label":748,"count":749},"data","Data",41,{"key":751,"label":752,"count":753},"insurance","Insurance",40,{"key":755,"label":756,"count":757},"data provider","Data Provider",21,{"key":759,"label":131,"count":760},"asset management",14,{"key":762,"label":763,"count":764},"banking","Banking",6,{"key":766,"label":767,"count":29},"alternative investments","Alternative Investments",{"key":769,"label":770,"count":28},"data services","Data Services",{"key":772,"label":773,"count":28},"fund administration","Fund Administration",{"key":775,"label":776,"count":28},"middle office","Middle Office",{"key":778,"label":779,"count":63},"financial market infrastructure","Financial Market Infrastructure",[781],{"key":26,"label":782,"count":783},"PERMANENT",227,[785,788,790,794,796,799,802,804,806,808,811,815,819,821,823,825,828,830,834,836,838,841,844,848],{"key":786,"label":129,"slug":786,"count":787},"data-analysis",34,{"key":789,"label":282,"slug":789,"count":787},"risk-management",{"key":791,"label":792,"slug":791,"count":793},"project-management","Project management",31,{"key":795,"label":188,"slug":795,"count":793},"data-engineering",{"key":797,"label":57,"slug":797,"count":798},"data-governance",28,{"key":800,"label":103,"slug":800,"count":801},"agile-methodologies",27,{"key":803,"label":61,"slug":803,"count":801},"process-improvement",{"key":805,"label":127,"slug":805,"count":757},"automation",{"key":807,"label":40,"slug":807,"count":757},"machine-learning",{"key":809,"label":222,"slug":809,"count":810},"data-modeling",20,{"key":812,"label":813,"slug":812,"count":814},"data-validation","Data Validation",18,{"key":816,"label":817,"slug":816,"count":818},"devops","Devops",17,{"key":820,"label":281,"slug":820,"count":818},"business-analysis",{"key":822,"label":50,"slug":822,"count":818},"data-analytics",{"key":824,"label":499,"slug":824,"count":818},"data-quality",{"key":826,"label":314,"slug":826,"count":827},"root-cause-analysis",16,{"key":829,"label":284,"slug":829,"count":827},"stakeholder-management",{"key":831,"label":832,"slug":831,"count":833},"regulatory-compliance","Regulatory Compliance",15,{"key":835,"label":223,"slug":835,"count":833},"technical-documentation",{"key":837,"label":56,"slug":837,"count":760},"data-management",{"key":839,"label":840,"slug":839,"count":760},"incident-management","Incident Management",{"key":842,"label":843,"slug":842,"count":760},"vendor-management","Vendor Management",{"key":845,"label":846,"slug":845,"count":847},"cicd","Ci\u002FCd",13,{"key":849,"label":850,"slug":849,"count":847},"generative-ai","Generative Ai",[852,854,857,861,864,866,869,872,875,878,882,885,887,889,892,894,897,901,904,906,909,912,914,917],{"key":853,"label":34,"slug":853,"count":4},"sql",{"key":855,"label":33,"slug":855,"count":856},"python",157,{"key":858,"label":859,"slug":858,"count":860},"aws","Aws",60,{"key":862,"label":78,"slug":862,"count":863},"java",55,{"key":845,"label":846,"slug":845,"count":865},43,{"key":867,"label":868,"slug":867,"count":749},"ms-powerbi","MS PowerBI",{"key":870,"label":91,"slug":870,"count":871},"git",37,{"key":873,"label":479,"slug":873,"count":874},"ms-excel",36,{"key":876,"label":96,"slug":876,"count":877},"jenkins",33,{"key":879,"label":880,"slug":879,"count":881},"ms-azure","MS Azure",30,{"key":883,"label":884,"slug":883,"count":798},"ai-tools","Ai Tools",{"key":886,"label":432,"slug":886,"count":798},"docker",{"key":888,"label":523,"slug":888,"count":798},"terraform",{"key":890,"label":175,"slug":890,"count":891},"snowflake",26,{"key":893,"label":38,"slug":893,"count":891},"tableau",{"key":895,"label":430,"slug":895,"count":896},"kubernetes",25,{"key":898,"label":899,"slug":898,"count":900},"vba","Vba",22,{"key":902,"label":903,"slug":902,"count":900},"oracle","Oracle",{"key":905,"label":173,"slug":905,"count":757},"databricks",{"key":907,"label":908,"slug":907,"count":757},"javascript","Javascript",{"key":910,"label":488,"slug":910,"count":911},"jira",19,{"key":913,"label":83,"slug":913,"count":814},"kafka",{"key":915,"label":916,"slug":915,"count":814},"pytorch","Pytorch",{"key":918,"label":919,"slug":918,"count":818},"rest-apis","Rest Apis",[921,923,924,926,928],{"key":22,"label":22,"count":922},175,{"key":557,"label":557,"count":749},{"key":239,"label":239,"count":925},8,{"key":927,"label":927,"count":30},"GBP",{"key":404,"label":404,"count":63},[930,931],{"key":25,"label":25,"count":4},{"key":241,"label":241,"count":63},{"total":933,"jobs":934},0,[]]