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.
Across 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.
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Skills Required
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related field
- 0-7 years of experience in data engineering, software engineering, or a related technical role
- Working knowledge of Python
- Working knowledge of SQL
- Working knowledge of Java (and/or)
- Basic understanding of ETL/ELT pipelines, data transformation, and data integration concepts
- Basic familiarity with data lakes, data warehouses, or lakehouse architectures
- Understanding of data quality, metadata, and governance concepts
- Exposure to big data or distributed processing tools such as Spark or Databricks
- Exposure to RAG, vector databases, semantic search, or knowledge graph concepts
- Familiarity with orchestration tools such as Airflow or similar platforms
State Street Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about State Street and has not been reviewed or approved by State Street.
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Retirement Support — Retirement support is framed as a standout component, highlighted by a 401(k) match described as 100% on the first 6% of base salary. This is positioned as a meaningful offset to less competitive cash compensation for some roles.
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Leave & Time Off Breadth — Leave and time off are portrayed as relatively robust, with references to multi-week vacation, paid holidays, sick time, and additional days tied to wellness or volunteering. This breadth is repeatedly treated as a tangible part of total rewards beyond base pay.
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Wellbeing & Lifestyle Benefits — Wellbeing and lifestyle benefits are presented as extensive, including the BeWell program, fitness discounts, onsite or supported health resources, and financial counseling. These offerings are depicted as strengthening the overall benefits proposition even when pay satisfaction is tepid.
State Street Insights
What We Do
At State Street, we partner with institutional investors all over the world to provide comprehensive financial services, including investment management, investment research and trading, and investment servicing. Whether you are an asset manager, asset owner, alternative asset manager, insurance company, pension fund or official institution, you can rely on us to be focused on your challenges. We are committed to doing what it takes to help you perform better — now and in the future
