AI Data & Knowledge Engineer – Senior Associate
State Street
AI Data & Knowledge Engineer – Senior Associate
Job Description
About the Role We are looking for an AI Data & Knowledge Engineer with a strong foundation in data engineering and an interest in AI-powered data systems. This role will help build and maintain scalable backend data pipelines, ETL/ELT workflows, and structured knowledge assets that power enterprise AI applications. The ideal candidate will contribute to big data processing, data integration, retrieval pipelines, and knowledge graph foundations that enable reliable GenAI use cases. Key Responsibilities Build and maintain backend data pipelines to ingest, transform, and serve structured and unstructured data for AI applications. Support ETL/ELT workflows across enterprise source systems, data platforms, and downstream AI services. Assist in developing RAG pipelines, vector indexing workflows, and knowledge graph assets under guidance from senior engineers. Contribute to data modeling, ontology creation, metadata tagging, and semantic enrichment of enterprise data. Support MCP server integration and AI data enablement tasks for domain use cases. Perform data quality checks, validation, reconciliation, and documentation for pipelines and data contracts. Help optimize pipeline performance, reliability, and scalability across batch and near-real-time workloads. Participate in code reviews, sprint ceremonies, and engineering discussions to build platform and domain knowledge. Required Qualifications Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field. 0–7 years of experience in data engineering, software engineering, or a related technical role. Working knowledge of Python and SQL and/or Java. Basic understanding of ETL/ELT pipelines, data transformation, and data integration concepts. Exposure to big data or distributed processing tools such as Spark, Databricks, or similar platforms is preferred. Basic familiarity with data lakes, warehouses, or lakehouse architectures. Understanding of data quality, metadata, and governance concepts. Exposure to RAG, vector databases, semantic search, or knowledge graph concepts is a plus. Familiarity with orchestration tools such as Airflow or similar platforms is beneficial. About State StreetAcross the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.Discover more information on jobs at StateStreet.com/careersRead our CEO Statement
Locations
- India, Bangalore
Skills Required
- data engineeringintermediate
- Pythonintermediate
- data lakesintermediate
- orchestration tools such as Airflowintermediate
Required Qualifications
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field. (degree in computer science)
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field. (degree in computer science)
- 0–7 years of experience in data engineering, software engineering, or a related technical role. (experience, 7 years)
- 0–7 years of experience in data engineering, software engineering, or a related technical role. (experience, 7 years)
- Working knowledge of Python and SQL and/or Java. (experience)
- Working knowledge of Python and SQL and/or Java. (experience)
- Basic understanding of ETL/ELT pipelines, data transformation, and data integration concepts. (experience)
- Basic understanding of ETL/ELT pipelines, data transformation, and data integration concepts. (experience)
- Exposure to big data or distributed processing tools such as Spark, Databricks, or similar platforms is preferred. (experience)
- Exposure to big data or distributed processing tools such as Spark, Databricks, or similar platforms is preferred. (experience)
- Basic familiarity with data lakes, warehouses, or lakehouse architectures. (experience)
- Basic familiarity with data lakes, warehouses, or lakehouse architectures. (experience)
- Understanding of data quality, metadata, and governance concepts. (experience)
- Understanding of data quality, metadata, and governance concepts. (experience)
- Exposure to RAG, vector databases, semantic search, or knowledge graph concepts is a plus. (experience)
- Exposure to RAG, vector databases, semantic search, or knowledge graph concepts is a plus. (experience)
- Familiarity with orchestration tools such as Airflow or similar platforms is beneficial. (experience)
- Familiarity with orchestration tools such as Airflow or similar platforms is beneficial. (experience)
Responsibilities
- Build and maintain backend data pipelines to ingest, transform, and serve structured and unstructured data for AI applications.
- Build and maintain backend data pipelines to ingest, transform, and serve structured and unstructured data for AI applications.
- Support ETL/ELT workflows across enterprise source systems, data platforms, and downstream AI services.
- Support ETL/ELT workflows across enterprise source systems, data platforms, and downstream AI services.
- Assist in developing RAG pipelines, vector indexing workflows, and knowledge graph assets under guidance from senior engineers.
- Assist in developing RAG pipelines, vector indexing workflows, and knowledge graph assets under guidance from senior engineers.
- Contribute to data modeling, ontology creation, metadata tagging, and semantic enrichment of enterprise data.
- Contribute to data modeling, ontology creation, metadata tagging, and semantic enrichment of enterprise data.
- Support MCP server integration and AI data enablement tasks for domain use cases.
- Support MCP server integration and AI data enablement tasks for domain use cases.
- Perform data quality checks, validation, reconciliation, and documentation for pipelines and data contracts.
- Perform data quality checks, validation, reconciliation, and documentation for pipelines and data contracts.
- Help optimize pipeline performance, reliability, and scalability across batch and near-real-time workloads.
- Help optimize pipeline performance, reliability, and scalability across batch and near-real-time workloads.
- Participate in code reviews, sprint ceremonies, and engineering discussions to build platform and domain knowledge.
- Participate in code reviews, sprint ceremonies, and engineering discussions to build platform and domain knowledge.
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