[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"seo-content-skill-neo4j-global":3,"skill-page-filters-\u002Fde-global\u002Fjobs-by-skill\u002Fneo4j":4,"job-search-\u002Fde-global\u002Fjobs-by-skill\u002Fneo4j":210,"featured-jobs-\u002Fde-global\u002Fjobs-by-skill\u002Fneo4j":788},{},{"industry":5,"employment_type":33,"expertise_skills":41,"it_skills":117,"salary_currency":194,"processed_working_hours":207},[6,10,13,16,20,24,27,30],{"key":7,"label":8,"count":9},"insurance","Insurance",6,{"key":11,"label":12,"count":9},"banking","Banking",{"key":14,"label":15,"count":9},"financial services","Financial Services",{"key":17,"label":18,"count":19},"compensation","Compensation",2,{"key":21,"label":22,"count":23},"fund administration","Fund Administration",1,{"key":25,"label":26,"count":23},"middle office","Middle Office",{"key":28,"label":29,"count":23},"tools","Tools",{"key":31,"label":32,"count":23},"software","Software",[34,38],{"key":35,"label":36,"count":37},"permanent","PERMANENT",14,{"key":39,"label":40,"count":19},"student","STUDENT",[42,46,49,52,56,59,62,65,68,72,75,78,81,84,87,90,93,96,99,102,105,108,111,114],{"key":43,"label":44,"slug":43,"count":45},"distributed-systems","Distributed Systems",5,{"key":47,"label":48,"slug":47,"count":45},"data-governance","Data Governance",{"key":50,"label":51,"slug":50,"count":45},"data-engineering","Data Engineering",{"key":53,"label":54,"slug":53,"count":55},"data-architecture","Data Architecture",4,{"key":57,"label":58,"slug":57,"count":55},"data-quality","Data Quality",{"key":60,"label":61,"slug":60,"count":55},"business-intelligence","Business Intelligence",{"key":63,"label":64,"slug":63,"count":55},"data-lineage","Data Lineage",{"key":66,"label":67,"slug":66,"count":55},"prompt-engineering","Prompt Engineering",{"key":69,"label":70,"slug":69,"count":71},"data-warehousing","Data Warehousing",3,{"key":73,"label":74,"slug":73,"count":71},"data-modeling","Data Modeling",{"key":76,"label":77,"slug":76,"count":71},"data-integration","Data Integration",{"key":79,"label":80,"slug":79,"count":71},"platform-engineering","Platform Engineering",{"key":82,"label":83,"slug":82,"count":19},"web-development","Web Development",{"key":85,"label":86,"slug":85,"count":19},"api-architecture","Api Architecture",{"key":88,"label":89,"slug":88,"count":19},"software-development","Software Development",{"key":91,"label":92,"slug":91,"count":19},"data-domains","Data Domains",{"key":94,"label":95,"slug":94,"count":19},"data-products","Data Products",{"key":97,"label":98,"slug":97,"count":19},"event-driven-architecture","Event-Driven Architecture",{"key":100,"label":101,"slug":100,"count":19},"regulatory-compliance","Regulatory Compliance",{"key":103,"label":104,"slug":103,"count":19},"fairness","Fairness",{"key":106,"label":107,"slug":106,"count":19},"transaction-banking","Transaction Banking",{"key":109,"label":110,"slug":109,"count":19},"eval-driven-development","Eval-Driven Development",{"key":112,"label":113,"slug":112,"count":19},"generative-ai","Generative Ai",{"key":115,"label":116,"slug":115,"count":19},"semantic-modeling","Semantic Modeling",[118,122,126,130,133,137,140,143,146,149,152,155,158,161,164,167,170,173,176,179,182,185,188,191],{"key":119,"label":120,"slug":119,"count":121},"neo4j","Neo4J",16,{"key":123,"label":124,"slug":123,"count":125},"python","Python",13,{"key":127,"label":128,"slug":127,"count":129},"mongodb","Mongodb",9,{"key":131,"label":132,"slug":131,"count":129},"java","Java",{"key":134,"label":135,"slug":134,"count":136},"sql","SQL",7,{"key":138,"label":139,"slug":138,"count":136},"snowflake","Snowflake",{"key":141,"label":142,"slug":141,"count":136},"ms-azure","MS Azure",{"key":144,"label":145,"slug":144,"count":9},"kubernetes","Kubernetes",{"key":147,"label":148,"slug":147,"count":9},"kafka","Kafka",{"key":150,"label":151,"slug":150,"count":45},"graphql","Graphql",{"key":153,"label":154,"slug":153,"count":45},"postgresql","Postgresql",{"key":156,"label":157,"slug":156,"count":55},"mcp","Mcp",{"key":159,"label":160,"slug":159,"count":55},"datadog","Datadog",{"key":162,"label":163,"slug":162,"count":55},"tensorflow","Tensorflow",{"key":165,"label":166,"slug":165,"count":55},"typescript","Typescript",{"key":168,"label":169,"slug":168,"count":55},"redis","Redis",{"key":171,"label":172,"slug":171,"count":55},"databricks","Databricks",{"key":174,"label":175,"slug":174,"count":55},"nosql","Nosql",{"key":177,"label":178,"slug":177,"count":55},"pytorch","Pytorch",{"key":180,"label":181,"slug":180,"count":55},"apache-spark","Apache Spark",{"key":183,"label":184,"slug":183,"count":55},"spark","Spark",{"key":186,"label":187,"slug":186,"count":55},"cicd","Ci\u002FCd",{"key":189,"label":190,"slug":189,"count":71},"aws","Aws",{"key":192,"label":193,"slug":192,"count":71},"langchain","Langchain",[195,197,199,201,203,205],{"key":196,"label":196,"count":55},"CAD",{"key":198,"label":198,"count":71},"EUR",{"key":200,"label":200,"count":71},"INR",{"key":202,"label":202,"count":71},"USD",{"key":204,"label":204,"count":19},"GBP",{"key":206,"label":206,"count":23},"MXN",[208],{"key":209,"label":209,"count":121},"FULL_TIME",{"total":121,"jobs":211},[212,279,325,379,411,468,495,521,553,574,598,626,667,692,715,768],{"id":213,"slug":214,"title":215,"raw_title":216,"is_featured":217,"company":218,"raw_hiringOrganization_logo_url":216,"processed_city_gmaps":221,"processed_country_iso_code_gmaps":223,"processed_home_office":225,"processed_salary_min":226,"processed_salary_max":227,"processed_salary_currency":200,"processed_salary_source":228,"processed_working_hours":229,"processed_employment_types":35,"processed_it_skills":230,"processed_it_skills_labels":231,"processed_job_expertise_skills":259,"processed_job_expertise_skills_labels":260,"max_cpc":23,"actual_cpc":23},83074,"data-science-and-ai-engineering-lead-vp-f337-deutsche-india-private-limited-pune-branch","Data Science and AI Engineering Lead​, VP",null,false,{"name":219,"slug":220,"logo_url":216},"F337 Deutsche India Private Limited, Pune Branch","f337-deutsche-india-private-limited-pune-branch",[222],"Pune",[224],"IN","hybrid",5000000,8000000,"estimated",[209],{"adk":55,"gke":55,"sql":71,"java":71,"flask":55,"neo4j":55,"redis":55,"spark":55,"denodo":55,"github":55,"looker":55,"mlflow":55,"python":55,"fastapi":55,"fastmcp":55,"mongodb":55,"pytorch":55,"vs code":55,"bigquery":55,"cloudsql":55,"pinecone":55,"langchain":55,"langgraph":55,"snowflake":55,"databricks":55,"postgresql":55,"tensorflow":55,"claude code":55,"gcp cloudrun":55,"hugging face":55,"scikit-learn":55,"cloud composer":55,"github copilot":55,"google vertexai":55,"jupyter notebook":55,"weights and biases":55},[124,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,193,120,247,248,249,250,251,252,253,254,184,255,169,172,256,139,135,132,257,258],"FastAPI","Flask","FastMcp","LangGraph","ADK","Google VertexAI","GitHub","VS Code","PyTorch","TensorFlow","scikit-learn","MLflow","Weights and Biases","Jupyter Notebook","Hugging Face","GCP CloudRun","GKE","BigQuery","Cloud Composer","CloudSQL","Looker","PostgreSQL","Pinecone","MongoDB","Denodo","Claude Code","GitHub Copilot",{"deployment":55,"roi analysis":71,"ai governance":55,"api architecture":55,"data engineering":55,"budget management":71,"people management":55,"ai risk management":55,"feature engineering":55,"ai model integration":55,"ai model optimization":55,"data product creation":55,"performance monitoring":55,"testing and validation":55,"research and innovation":55,"ai solution architecture":55,"cross-functional collaboration":55,"cloud infrastructure management":55,"software development lifecycle (sdlc)":55},[261,262,263,264,265,266,267,268,51,269,270,271,272,273,274,275,276,277,278],"AI Solution Architecture","AI Model Integration","AI Model Optimization","API Architecture","Cloud Infrastructure Management","AI Governance","AI Risk Management","Software Development Lifecycle (SDLC)","Feature Engineering","Data Product Creation","Performance Monitoring","Testing and Validation","Deployment","Research and Innovation","Cross-Functional Collaboration","People Management","Budget Management","ROI Analysis",{"id":280,"slug":281,"title":282,"raw_title":216,"is_featured":217,"company":283,"raw_hiringOrganization_logo_url":216,"processed_city_gmaps":286,"processed_country_iso_code_gmaps":288,"processed_home_office":225,"processed_salary_min":290,"processed_salary_max":291,"processed_salary_currency":202,"processed_salary_source":228,"processed_working_hours":292,"processed_employment_types":35,"processed_it_skills":293,"processed_it_skills_labels":294,"processed_job_expertise_skills":303,"processed_job_expertise_skills_labels":304,"max_cpc":23,"actual_cpc":23},83786,"senior-staff-ml-engineer-government-employees-insurance-company","Senior Staff ML Engineer",{"name":284,"slug":285,"logo_url":216},"Government Employees Insurance Company","government-employees-insurance-company",[287],"Palo Alto",[289],"US",150000,300000,[209],{"aws":71,"dbt":71,"java":55,"azure":71,"neo4j":71,"redis":71,"spark":71,"python":55,"airflow":71,"mongodb":71,"pytorch":71,"azure ml":71,"sagemaker":71,"snowflake":71,"kubernetes":71,"tensorflow":71,"scikit-learn":71},[124,132,295,296,145,184,255,139,297,169,298,299,300,301,241,240,302],"Airflow","DBT","Neo4j","AWS","Azure","SageMaker","Azure ML","Scikit-learn",{"rag":71,"fairness":55,"fine-tuning":71,"risk modeling":55,"explainability":55,"llm deployment":71,"bias mitigation":55,"cloud platforms":55,"fraud detection":55,"digital identity":55,"machine learning":55,"model governance":55,"trust and safety":55,"big data technologies":55,"graph neural networks":71,"regulatory compliance":55,"model interpretability":55,"artificial intelligence":55,"aiml lifecycle management":55,"large-scale data pipelines":55,"backend distributed systems":55,"real-time aiml serving architectures":55},[305,306,307,308,309,310,311,312,313,314,315,316,317,104,101,318,319,320,321,322,323,324],"Machine Learning","Artificial Intelligence","Fraud Detection","Risk Modeling","Trust and Safety","Digital Identity","Large-scale Data Pipelines","Real-time AIML Serving Architectures","AIML Lifecycle Management","Backend Distributed Systems","Big Data Technologies","Cloud Platforms","Model Interpretability","Model Governance","Explainability","Bias Mitigation","LLM Deployment","RAG","Fine-tuning","Graph Neural Networks",{"id":326,"slug":327,"title":328,"raw_title":216,"is_featured":217,"company":329,"raw_hiringOrganization_logo_url":332,"processed_city_gmaps":333,"processed_country_iso_code_gmaps":335,"processed_home_office":225,"processed_salary_min":337,"processed_salary_max":338,"processed_salary_currency":204,"processed_salary_source":339,"processed_working_hours":340,"processed_employment_types":35,"processed_it_skills":341,"processed_it_skills_labels":342,"processed_job_expertise_skills":364,"processed_job_expertise_skills_labels":365,"max_cpc":23,"actual_cpc":23},84459,"staff-software-engineer-ravio-2","Staff Software Engineer",{"name":330,"slug":331,"logo_url":216},"Ravio","ravio","https:\u002F\u002Fapp.ashbyhq.com\u002Fapi\u002Fimages\u002Forg-theme-logo\u002F967f3421-4458-498b-b3fe-910182b0a3f8\u002F8e491013-1614-4a48-a8f5-75d1b32c3074\u002Ffd50ac96-be87-4067-bbb0-d4e517a29b2b.png",[334],"London",[336],"GB",110000,170000,"original",[209],{"gcp":55,"mcp":71,"jest":19,"auth0":19,"figma":19,"neo4j":19,"react":71,"slack":19,"linear":19,"bifrost":19,"datadog":19,"graphql":55,"mantine":19,"node.js":55,"phoenix":19,"temporal":71,"chromatic":19,"llm evals":71,"storybook":19,"playwright":19,"postgresql":55,"typescript":55,"anthropic sdk":71,"github actions":19},[343,344,253,345,346,347,348,349,350,351,352,353,354,355,356,357,358,160,359,360,361,297,362,363],"TypeScript","Node.js","GraphQL","GCP","React","Temporal","MCP","Anthropic SDK","LLM evals","Playwright","Jest","Storybook","Chromatic","Mantine","Auth0","GitHub Actions","Figma","Slack","Linear","Bifrost","Phoenix",{"code review":55,"design review":55,"observability":55,"system design":55,"data platforms":55,"agentic systems":71,"workflow engines":71,"cost optimization":55,"prompt engineering":71,"developer platforms":71,"distributed systems":55,"platform engineering":55,"software architecture":55,"eval-driven development":71,"performance optimization":55,"durability and consistency":55,"multi-service orchestration":55},[366,367,44,80,368,369,370,110,67,371,372,373,374,375,376,377,378],"System Design","Software Architecture","Agentic Systems","Workflow Engines","Developer Platforms","Code Review","Design Review","Observability","Performance Optimization","Cost Optimization","Multi-Service Orchestration","Data Platforms","Durability and Consistency",{"id":380,"slug":381,"title":382,"raw_title":216,"is_featured":217,"company":383,"raw_hiringOrganization_logo_url":216,"processed_city_gmaps":386,"processed_country_iso_code_gmaps":388,"processed_home_office":390,"processed_salary_min":291,"processed_salary_max":391,"processed_salary_currency":206,"processed_salary_source":228,"processed_working_hours":392,"processed_employment_types":35,"processed_it_skills":393,"processed_it_skills_labels":394,"processed_job_expertise_skills":399,"processed_job_expertise_skills_labels":400,"max_cpc":23,"actual_cpc":23},69566,"aml-compliance-associate-ciclo-y-analitica-investigations-ciudad-de-mexico-cuauhtemoc-bbva-mexico-sa","AML Compliance Associate Ciclo y Analítica (Investigations) (Ciudad de México, Cuauhtemoc)",{"name":384,"slug":385,"logo_url":216},"BBVA MÉXICO S.A.","bbva-mexico-sa",[387],"Mexiko-Stadt",[389],"MX","onsite",500000,[209],{"neo4j":19,"python":19,"maltego":71,"microsoft azure ai":19,"google ai essentials":19,"ibm i2 analyst's notebook":71},[124,297,395,396,397,398],"IBM i2 Analyst's Notebook","Maltego","Microsoft Azure AI","Google AI Essentials",{"graph theory":55,"link analysis":55,"osint analysis":55,"fraud prevention":55,"forensic analysis":55,"financial investigation":55,"corporate deconstruction":55,"anti-money laundering (aml)":55,"forensic narrative and evidentiary documentation":55,"ultimate beneficial ownership (ubo) identification":55},[401,402,403,404,405,406,407,408,409,410],"Link Analysis","Graph Theory","Corporate Deconstruction","Ultimate Beneficial Ownership (UBO) Identification","OSINT Analysis","Anti-Money Laundering (AML)","Fraud Prevention","Forensic Narrative and Evidentiary Documentation","Financial Investigation","Forensic Analysis",{"id":412,"slug":413,"title":414,"raw_title":216,"is_featured":217,"company":415,"raw_hiringOrganization_logo_url":216,"processed_city_gmaps":418,"processed_country_iso_code_gmaps":420,"processed_home_office":225,"processed_salary_min":421,"processed_salary_max":422,"processed_salary_currency":200,"processed_salary_source":228,"processed_working_hours":423,"processed_employment_types":35,"processed_it_skills":424,"processed_it_skills_labels":425,"processed_job_expertise_skills":454,"processed_job_expertise_skills_labels":455,"max_cpc":23,"actual_cpc":23},78821,"ind-senior-engineer-data-hartford-global-services-private-limited","IND Senior Engineer, Data",{"name":416,"slug":417,"logo_url":216},"Hartford Global Services Private Limited","hartford-global-services-private-limited",[419],"Hyderabad",[224],2500000,4000000,[209],{"a2a":55,"aws":55,"mcp":55,"rdf":55,"sql":55,"azure":55,"ci\u002Fcd":55,"neo4j":55,"nosql":55,"spark":55,"aws s3":55,"cypher":55,"docker":55,"python":55,"sparql":55,"aws ec2":55,"mongodb":55,"pytorch":71,"big data":55,"dynamodb":55,"data lake":55,"data mesh":55,"langchain":55,"langgraph":55,"snowflake":55,"aws lambda":55,"kubernetes":55,"tensorflow":71,"aws kinesis":55,"data fabric":55,"apache kafka":55,"document dbs":55,"etl\u002Felt tools":55,"gcp vertex ai":55,"spanner graph":55,"amazon neptune":55,"aws opensearch":55,"graph databases":55,"spark streaming":55,"vector databases":55,"google cloud platform":55},[426,427,428,135,429,139,430,431,432,298,433,299,124,184,434,435,436,437,145,240,241,438,439,440,441,442,297,443,444,255,445,446,447,448,449,235,349,450,451,452,453],"Apache Kafka","AWS Kinesis","Spark Streaming","NoSQL","ETL\u002FELT tools","CI\u002FCD","Big Data","Google Cloud Platform","Data Mesh","Data Lake","Data Fabric","Docker","Vector Databases","Graph Databases","Document DBs","AWS OpenSearch","GCP Vertex AI","Spanner Graph","Amazon Neptune","DynamoDB","AWS Lambda","AWS S3","AWS EC2","LangChain","A2A","Cypher","SPARQL","RDF",{"devops":55,"data lakes":55,"data domains":55,"data lineage":55,"data quality":55,"scaled agile":55,"data products":55,"generative ai":55,"data catalogue":55,"data governance":55,"cloud technology":55,"data engineering":55,"data integration":55,"data warehousing":55,"knowledge graphs":55,"data architecture":55,"semantic modeling":55,"prompt engineering":55,"business intelligence":55,"reliability engineering":55,"synthetic data generation":55,"ai-driven data engineering":55,"insurance domain knowledge":71,"retrieval-augmented generation (rag)":55},[51,54,70,77,456,92,95,61,457,458,459,67,116,460,461,48,58,64,462,463,464,465,466,467],"Data Lakes","Cloud Technology","Generative AI","Retrieval-Augmented Generation (RAG)","Knowledge Graphs","Synthetic Data Generation","Data Catalogue","AI-driven Data Engineering","DevOps","Reliability Engineering","Scaled Agile","Insurance Domain Knowledge",{"id":469,"slug":470,"title":471,"raw_title":216,"is_featured":217,"company":472,"raw_hiringOrganization_logo_url":216,"processed_city_gmaps":475,"processed_country_iso_code_gmaps":476,"processed_home_office":390,"processed_salary_min":477,"processed_salary_max":478,"processed_salary_currency":202,"processed_salary_source":228,"processed_working_hours":479,"processed_employment_types":35,"processed_it_skills":480,"processed_it_skills_labels":481,"processed_job_expertise_skills":485,"processed_job_expertise_skills_labels":486,"max_cpc":23,"actual_cpc":23},69193,"knowledge-engineer-associated-bank-na","Knowledge Engineer",{"name":473,"slug":474,"logo_url":216},"Associated Bank, NA","associated-bank-na",[],[],92610,158760,[209],{"neo4j":71,"snowflake":71,"data lineage":71,"data modeling":55,"graph databases":55,"metadata management":71,"data governance tools":71,"semantic web standards":55},[297,139,439,482,74,483,64,484],"Semantic Web Standards","Metadata Management","Data Governance Tools",{"data engineering":71,"data architecture":71,"ai data capabilities":71,"ontology development":55,"taxonomy development":55,"semantic technologies":55,"data quality initiatives":71,"knowledge representation":55,"enterprise data governance":71,"knowledge graph implementation":55},[487,488,489,490,491,492,493,54,51,494],"Semantic Technologies","Knowledge Representation","Ontology Development","Taxonomy Development","Knowledge Graph Implementation","Enterprise Data Governance","Data Quality Initiatives","AI Data Capabilities",{"id":496,"slug":497,"title":498,"raw_title":216,"is_featured":217,"company":499,"raw_hiringOrganization_logo_url":216,"processed_city_gmaps":500,"processed_country_iso_code_gmaps":501,"processed_home_office":225,"processed_salary_min":502,"processed_salary_max":226,"processed_salary_currency":200,"processed_salary_source":228,"processed_working_hours":503,"processed_employment_types":35,"processed_it_skills":504,"processed_it_skills_labels":505,"processed_job_expertise_skills":507,"processed_job_expertise_skills_labels":508,"max_cpc":23,"actual_cpc":23},78805,"ind-lead-engineer-data-hartford-global-services-private-limited","IND Lead Engineer, Data",{"name":416,"slug":417,"logo_url":216},[419],[224],3000000,[209],{"a2a":55,"mcp":55,"rdf":55,"sql":55,"ci\u002Fcd":55,"neo4j":55,"nosql":55,"aws s3":55,"cypher":55,"docker":55,"python":55,"sparql":55,"aws ec2":55,"mongodb":55,"pytorch":71,"big data":55,"dynamodb":55,"langchain":55,"langgraph":55,"snowflake":55,"aws lambda":55,"kubernetes":55,"tensorflow":71,"aws kinesis":55,"apache kafka":55,"apache spark":55,"etl\u002Felt tools":55,"gcp vertex ai":55,"spanner graph":55,"amazon neptune":55,"aws opensearch":55,"graph databases":55,"vector databases":55,"cloud technologies (aws\u002Fgcp\u002Fazure)":55},[124,135,429,139,430,431,432,506,181,426,427,437,145,240,241,438,439,297,444,255,445,446,447,448,449,235,349,450,451,452,453,441,442,443],"Cloud Technologies (AWS\u002FGCP\u002FAzure)",{"ai\u002Fml":55,"devops":55,"alerting":55,"analytics":55,"data mesh":55,"data lakes":55,"monitoring":55,"redundancy":55,"data fabric":55,"data catalog":55,"data domains":55,"data lineage":55,"data quality":55,"scaled agile":55,"data products":55,"generative ai":55,"data governance":55,"fault tolerance":55,"data engineering":55,"data integration":55,"data warehousing":55,"knowledge graphs":55,"agentic solutions":55,"data architecture":55,"disaster recovery":55,"semantic modeling":55,"prompt engineering":55,"incident management":55,"business intelligence":55,"reliability engineering":55,"real-time data streaming":55,"synthetic data generation":55,"insurance domain knowledge":71,"unstructured data processing":55,"retrieval-augmented generation (rag)":55},[51,54,70,77,456,92,95,61,48,58,64,509,458,459,67,116,460,461,510,466,464,465,511,512,513,514,515,516,434,436,517,518,519,520,467],"Data Catalog","Agentic Solutions","Disaster Recovery","Fault Tolerance","Redundancy","Monitoring","Alerting","Incident Management","Unstructured Data Processing","Real-Time Data Streaming","AI\u002FML","Analytics",{"id":522,"slug":523,"title":524,"raw_title":216,"is_featured":217,"company":525,"raw_hiringOrganization_logo_url":528,"processed_city_gmaps":529,"processed_country_iso_code_gmaps":531,"processed_home_office":390,"processed_salary_min":533,"processed_salary_max":533,"processed_salary_currency":198,"processed_salary_source":228,"processed_working_hours":534,"processed_employment_types":39,"processed_it_skills":535,"processed_it_skills_labels":536,"processed_job_expertise_skills":545,"processed_job_expertise_skills_labels":546,"max_cpc":23,"actual_cpc":23},74611,"abschlussarbeiten-in-der-itlvm-beginn-2027-heike-franke","Abschlussarbeiten in der IT@LVM - Beginn 2027",{"name":526,"slug":527,"logo_url":216},"LVM-Versicherung","lvm-versicherung","https:\u002F\u002Fd1m3qravo0uxtt.cloudfront.net\u002Fimage\u002F346054306320\u002Fimage_jcirioducl34982mqb20jru124\u002F-FPNG-S500\u002Flvm_logo.png",[530],"Münster",[532],"DE",16800,[209],{"db2":71,"sas":71,"java":71,"kafka":71,"mysql":71,"neo4j":71,"redis":71,"python":71,"spring":71,"angular":71,"teradata":71,"postgresql":71,"springboot":71,"typescript":71,"informatica":71},[132,537,538,343,539,148,253,540,541,297,169,124,542,543,544],"Spring","SpringBoot","Angular","MySQL","DB2","SAS","Informatica","Teradata",{"usability":71,"ux design":71,"it security":71,"data warehouse":71,"web development":71,"software development":71,"business intelligence":71,"database architecture":71,"it infrastructure development":71},[89,83,547,548,549,61,550,551,552],"IT Infrastructure Development","IT Security","Database Architecture","Data Warehouse","UX Design","Usability",{"id":554,"slug":555,"title":556,"raw_title":216,"is_featured":217,"company":557,"raw_hiringOrganization_logo_url":528,"processed_city_gmaps":558,"processed_country_iso_code_gmaps":559,"processed_home_office":390,"processed_salary_min":560,"processed_salary_max":561,"processed_salary_currency":198,"processed_salary_source":228,"processed_working_hours":562,"processed_employment_types":39,"processed_it_skills":563,"processed_it_skills_labels":564,"processed_job_expertise_skills":569,"processed_job_expertise_skills_labels":570,"max_cpc":23,"actual_cpc":23},74682,"hochschulpraktika-in-der-itlvm-beginn-2027-heike-franke","Hochschulpraktika in der IT@LVM - Beginn 2027",{"name":526,"slug":527,"logo_url":216},[530],[532],18000,24000,[209],{"db2":19,"ios":19,"sas":19,"java":19,"z\u002Fos":19,"kafka":19,"mysql":19,"neo4j":19,"redis":19,"python":19,"spring":19,"android":19,"angular":19,"teradata":19,"usability":19,"ux design":19,"postgresql":19,"typescript":19,"informatica":19,"spring boot":19,"machine learning":19},[132,537,565,343,539,566,567,148,253,540,541,297,169,568,305,542,543,544,124,551,552],"Spring Boot","Android","iOS","z\u002FOS",{"it security":19,"data warehouse":19,"internal audit":19,"app development":19,"web development":19,"system development":19,"software development":19,"business intelligence":19,"database architecture":19,"it infrastructure development":19},[89,83,571,547,548,549,572,61,550,573],"App Development","System Development","Internal Audit",{"id":575,"slug":576,"title":577,"raw_title":216,"is_featured":217,"company":578,"raw_hiringOrganization_logo_url":216,"processed_city_gmaps":579,"processed_country_iso_code_gmaps":580,"processed_home_office":225,"processed_salary_min":581,"processed_salary_max":582,"processed_salary_currency":202,"processed_salary_source":228,"processed_working_hours":583,"processed_employment_types":35,"processed_it_skills":584,"processed_it_skills_labels":585,"processed_job_expertise_skills":588,"processed_job_expertise_skills_labels":589,"max_cpc":23,"actual_cpc":23},83772,"distinguished-engineer-ai-applications-government-employees-insurance-company-2","Distinguished Engineer, AI Applications",{"name":284,"slug":285,"logo_url":216},[287],[289],210000,350000,[209],{"aws":55,"dbt":55,"java":55,"azure":55,"neo4j":55,"spark":55,"python":55,"airflow":55,"mongodb":55,"azure ml":55,"sagemaker":55,"snowflake":55,"aws bedrock":55,"elasticsearch":55},[124,132,296,295,184,255,586,139,297,298,299,300,301,587],"ElasticSearch","AWS Bedrock",{"fairness":55,"security":55,"explainability":55,"data governance":55,"machine learning":55,"model monitoring":55,"scalable systems":55,"model maintenance":55,"strategic planning":55,"architecture design":55,"real-time ml serving":55,"regulatory compliance":55,"model interpretability":55,"large-scale data pipelines":55,"cross-functional leadership":55},[305,48,590,101,317,104,319,591,592,593,594,595,596,597,311],"Security","Model Monitoring","Model Maintenance","Scalable Systems","Cross-functional Leadership","Strategic Planning","Architecture Design","Real-time ML Serving",{"id":599,"slug":600,"title":601,"raw_title":216,"is_featured":217,"company":602,"raw_hiringOrganization_logo_url":216,"processed_city_gmaps":605,"processed_country_iso_code_gmaps":607,"processed_home_office":390,"processed_salary_min":609,"processed_salary_max":610,"processed_salary_currency":196,"processed_salary_source":228,"processed_working_hours":611,"processed_employment_types":35,"processed_it_skills":612,"processed_it_skills_labels":613,"processed_job_expertise_skills":619,"processed_job_expertise_skills_labels":620,"max_cpc":23,"actual_cpc":23},66814,"principal-platform-engineer-the-toronto-dominion-bank-canada","Principal Platform Engineer",{"name":603,"slug":604,"logo_url":216},"The Toronto-Dominion Bank (Canada)","the-toronto-dominion-bank-canada",[606],"Toronto",[608],"CA",165000,200000,[209],{"sql":55,"java":55,"llms":71,"mtls":55,"oidc":55,"rest":55,"azure":55,"neo4j":71,"nosql":55,"oauth2":55,"python":71,"graphql":55,"mongodb":71,"kubernetes":55,"generative ai":71},[132,124,145,299,614,345,135,429,255,120,615,616,617,458,618],"REST","OAuth2","mTLS","OIDC","LLMs",{"data modeling":55,"cash management":19,"api architecture":55,"distributed systems":55,"transaction banking":19,"platform engineering":55,"technical leadership":55,"graph-based data models":55,"event-driven integration":55,"cloud-native application delivery":55},[80,264,621,74,622,44,623,624,625,107],"Event-Driven Integration","Graph-Based Data Models","Cloud-Native Application Delivery","Technical Leadership","Cash Management",{"id":627,"slug":628,"title":629,"raw_title":216,"is_featured":217,"company":630,"raw_hiringOrganization_logo_url":216,"processed_city_gmaps":631,"processed_country_iso_code_gmaps":632,"processed_home_office":390,"processed_salary_min":609,"processed_salary_max":610,"processed_salary_currency":196,"processed_salary_source":228,"processed_working_hours":633,"processed_employment_types":35,"processed_it_skills":634,"processed_it_skills_labels":635,"processed_job_expertise_skills":649,"processed_job_expertise_skills_labels":650,"max_cpc":23,"actual_cpc":23},66714,"principal-engineer-gtb-data-and-platforms-the-toronto-dominion-bank-canada","Principal Engineer - GTB Data and Platforms",{"name":603,"slug":604,"logo_url":216},[606],[608],[209],{"mq":55,"ecs":55,"sql":55,"java":55,"llms":71,"ci\u002Fcd":55,"genai":71,"kafka":55,"neo4j":55,"nosql":55,"kibana":55,"oracle":55,"python":55,"solace":55,"splunk":55,"datadog":55,"graphql":55,"mongodb":55,"confluent":55,"dynatrace":55,"openshift":55,"databricks":55,"kubernetes":55,"spring boot":55,"apache flink":55,"apache spark":55,"restful apis":55,"microsoft azure":55},[132,124,636,345,565,135,637,429,255,120,181,172,148,638,639,640,641,145,642,643,431,644,645,646,160,647,648,618],"RESTful APIs","Oracle","Solace","MQ","Confluent","Apache Flink","OpenShift","ECS","Splunk","Kibana","Dynatrace","Microsoft Azure","GenAI",{"scrum":55,"data modeling":55,"system design":55,"devops practices":55,"stream processing":55,"big data platforms":55,"agile methodologies":55,"architecture design":55,"distributed systems":55,"platform resilience":55,"graph-based data models":55,"multi-cloud environments":55,"technical debt management":55,"event-driven architectures":55,"non-functional requirements":55,"cash management\u002Ftransaction banking":71},[651,652,653,654,655,656,657,658,659,660,661,662,663,664,665,666],"Data modeling","Graph-based data models","Big data platforms","Event-driven architectures","Stream processing","Distributed systems","System design","Non-functional requirements","Technical debt management","Platform resilience","Architecture design","Agile methodologies","Scrum","DevOps practices","Multi-cloud environments","Cash Management\u002FTransaction Banking",{"id":668,"slug":669,"title":670,"raw_title":216,"is_featured":217,"company":671,"raw_hiringOrganization_logo_url":216,"processed_city_gmaps":672,"processed_country_iso_code_gmaps":673,"processed_home_office":390,"processed_salary_min":674,"processed_salary_max":675,"processed_salary_currency":196,"processed_salary_source":228,"processed_working_hours":676,"processed_employment_types":35,"processed_it_skills":677,"processed_it_skills_labels":678,"processed_job_expertise_skills":680,"processed_job_expertise_skills_labels":681,"max_cpc":23,"actual_cpc":23},66748,"data-architect-the-toronto-dominion-bank-canada","Data Architect",{"name":603,"slug":604,"logo_url":216},[606],[608],125500,148000,[209],{"sql":71,"kafka":55,"neo4j":19,"python":71,"mongodb":19,"confluent":55,"databricks":55,"delta lake":55,"apache flink":71,"apache spark":55,"microsoft azure":55},[181,172,679,148,640,641,647,135,124,120,255],"Delta Lake",{"data mesh":71,"devsecops":55,"data lineage":55,"data quality":55,"data modeling":55,"model serving":71,"feature stores":71,"data governance":55,"llm integration":71,"vector databases":71,"data architecture":55,"metadata management":55,"regulatory reporting":71,"ai\u002Fml platform patterns":71,"enterprise architecture":55,"ci\u002Fcd for data pipelines":55,"event-driven architecture":55,"real-time data processing":55,"cloud-native data platform delivery":55},[54,74,48,64,483,58,434,98,682,683,684,685,686,438,687,688,689,690,691],"Real-Time Data Processing","Regulatory Reporting","AI\u002FML Platform Patterns","Feature Stores","Model Serving","LLM Integration","DevSecOps","CI\u002FCD for Data Pipelines","Enterprise Architecture","Cloud-Native Data Platform Delivery",{"id":693,"slug":694,"title":695,"raw_title":216,"is_featured":217,"company":696,"raw_hiringOrganization_logo_url":216,"processed_city_gmaps":697,"processed_country_iso_code_gmaps":698,"processed_home_office":390,"processed_salary_min":609,"processed_salary_max":610,"processed_salary_currency":196,"processed_salary_source":228,"processed_working_hours":699,"processed_employment_types":35,"processed_it_skills":700,"processed_it_skills_labels":701,"processed_job_expertise_skills":702,"processed_job_expertise_skills_labels":703,"max_cpc":23,"actual_cpc":23},66755,"director-data-platform-engineering-the-toronto-dominion-bank-canada","Director, Data Platform Engineering",{"name":603,"slug":604,"logo_url":216},[606],[608],[209],{"java":71,"llms":71,"rest":71,"ci\u002Fcd":55,"kafka":71,"neo4j":19,"python":71,"solace":71,"splunk":19,"datadog":19,"graphql":71,"mongodb":19,"confluent":71,"devsecops":55,"dynatrace":19,"openshift":19,"databricks":55,"delta lake":55,"kubernetes":71,"apache flink":71,"apache spark":55,"generative ai":71,"microsoft azure":55},[172,181,679,132,124,614,345,145,647,148,640,638,641,120,255,644,646,160,642,431,688,458,618],{"data lineage":55,"data quality":55,"microservices":71,"data governance":55,"risk management":55,"data engineering":55,"budget management":55,"vendor management":55,"financial services":71,"project management":55,"workforce planning":55,"agile methodologies":71,"distributed systems":55,"metadata management":55,"transaction banking":71,"regulatory reporting":71,"succession management":55,"performance management":55,"cloud-native architecture":55,"data lifecycle management":55,"event-driven architecture":55,"data platform architecture":55},[704,51,44,705,706,98,48,483,64,58,707,277,708,709,710,711,712,713,714,15,107,683],"Data Platform Architecture","Cloud-Native Architecture","Microservices","Data Lifecycle Management","Vendor Management","Workforce Planning","Succession Management","Performance Management","Risk Management","Project Management","Agile Methodologies",{"id":716,"slug":717,"title":718,"raw_title":216,"is_featured":217,"company":719,"raw_hiringOrganization_logo_url":216,"processed_city_gmaps":723,"processed_country_iso_code_gmaps":725,"processed_home_office":390,"processed_salary_min":727,"processed_salary_max":728,"processed_salary_currency":198,"processed_salary_source":228,"processed_working_hours":729,"processed_employment_types":35,"processed_it_skills":730,"processed_it_skills_labels":731,"processed_job_expertise_skills":758,"processed_job_expertise_skills_labels":759,"max_cpc":23,"actual_cpc":23},44460,"senior-data-pipeline-developer-apex-fund-services-bulgaria-eood-eur","Senior Data Pipeline Developer",{"name":720,"slug":721,"logo_url":722},"Apex Fund Services (Bulgaria) EOOD","apex-fund-services-bulgaria-eood","https:\u002F\u002Fwww.apexgroup.com\u002Fmedia\u002Fl05krqrh\u002Fapex-logo.svg",[724],"Sofia",[726],"BG",60000,90000,[209],{"sql":55,"java":71,"mode":19,"ssas":19,"ssis":19,"ssrs":19,"kafka":19,"neo4j":23,"scala":71,"python":55,"stitch":19,"camunda":19,"aws glue":71,"fivetran":19,"power bi":71,"rabbitmq":19,"azure asq":19,"snowflake":71,"aws lambda":71,"quicksight":19,"sql server":71,"aws neptune":23,"aws redshift":71,"aws sns & sqs":19,"azure synapse":71,"api management":19,"azure cosmos db":23,"azure data lake":71,"azure functions":71,"azure logic apps":19,"aws lake formation":71,"aws step functions":19,"azure data factory":71},[135,124,732,132,733,734,735,736,737,738,739,740,139,741,742,148,743,744,745,746,446,747,748,749,750,751,752,753,754,755,756,297,757],"Scala","AWS Glue","Azure Data Factory","Fivetran","Stitch","AWS Lake Formation","Azure Data Lake","AWS Redshift","Azure Synapse","AWS SNS & SQS","Azure ASQ","RabbitMQ","AWS Step Functions","Azure Logic Apps","Camunda","Azure Functions","SQL Server","SSIS","SSAS","SSRS","Power BI","QuickSight","Mode","AWS Neptune","Azure Cosmos DB","API Management",{"etl\u002Felt":55,"data models":55,"data modelling":55,"data pipelines":55,"api development":71,"data integration":55,"data preparation":55,"data warehousing":55,"analytical and reporting marts":55,"agile software development lifecycle":71},[70,760,761,762,77,763,764,765,766,767],"Data Modelling","ETL\u002FELT","Data Pipelines","Data Preparation","Data Models","Analytical and Reporting Marts","Agile Software Development Lifecycle","API Development",{"id":769,"slug":770,"title":771,"raw_title":216,"is_featured":217,"company":772,"raw_hiringOrganization_logo_url":332,"processed_city_gmaps":773,"processed_country_iso_code_gmaps":774,"processed_home_office":225,"processed_salary_min":337,"processed_salary_max":290,"processed_salary_currency":204,"processed_salary_source":339,"processed_working_hours":775,"processed_employment_types":35,"processed_it_skills":776,"processed_it_skills_labels":777,"processed_job_expertise_skills":783,"processed_job_expertise_skills_labels":784,"max_cpc":23,"actual_cpc":787},43011,"lead-software-engineer-ravio-2","Lead Software Engineer",{"name":330,"slug":331,"logo_url":216},[334],[336],[209],{"gcp":55,"mcp":71,"jest":71,"auth0":71,"figma":19,"neo4j":19,"react":71,"slack":19,"linear":19,"bedrock":19,"bifrost":19,"datadog":71,"foundry":19,"graphql":55,"mantine":19,"node.js":55,"phoenix":19,"temporal":71,"chromatic":19,"storybook":19,"vertex ai":19,"playwright":71,"postgresql":55,"typescript":55,"graphql yoga":71,"apollo client":71,"github actions":71},[343,344,253,345,347,352,353,354,355,356,346,357,348,349,297,358,160,359,360,361,778,779,780,781,782,362,363],"Apollo Client","GraphQL Yoga","Vertex AI","Bedrock","Foundry",{"llm evals":71,"observability":55,"agentic systems":71,"workflow engines":71,"prompt engineering":71,"distributed systems":55,"performance at scale":55,"platform engineering":55,"eval-driven development":71},[368,369,785,67,110,80,44,373,786],"LLM Evals","Performance at Scale",0.5,{"total":23,"jobs":789},[790],{"id":791,"slug":792,"title":793,"raw_title":216,"is_featured":794,"company":795,"raw_hiringOrganization_logo_url":216,"processed_city_gmaps":799,"processed_country_iso_code_gmaps":801,"processed_home_office":802,"processed_salary_min":803,"processed_salary_max":804,"processed_salary_currency":198,"processed_salary_source":216,"processed_working_hours":805,"processed_employment_types":36,"processed_it_skills":807,"processed_it_skills_labels":216,"processed_job_expertise_skills":808,"processed_job_expertise_skills_labels":809,"max_cpc":815,"actual_cpc":216},52265,"privatkundenbetreuer-mwd-banking-frankfurt-am-main-white-horse-international-gmbh","Privatkundenbetreuer (m\u002Fw\u002Fd) – Banking | Frankfurt am Main",true,{"name":796,"slug":797,"logo_url":798},"White Horse International GmbH","white-horse-international-gmbh","https:\u002F\u002Fwhitehorse-international.com\u002Fwp-content\u002Fuploads\u002F2022\u002F03\u002Fwhite-horse-logo-final-gif.gif",[800],"Frankfurt am Main",[532],"HYBRID",45000,65000,[806],"full_time",{},{"Financial Analysis":71,"Regulatory Compliance":71,"New Customer Acquisition":71,"Private Banking Advisory":71,"Banking Products Knowledge":71,"Customer Relationship Management":71},[810,811,812,101,813,814],"Private Banking Advisory","Financial Analysis","Banking Products Knowledge","Customer Relationship Management","New Customer Acquisition",0.8]