Distinguished Data Engineer

About the Opportunity Job Type: Permanent Application Deadline: 24 September 2026 Job Description Title                  Distinguished Data Engineer Department       AMP Location           Bengaluru Reports To        Research & Sustainable Investing Data Engineering Lead Level                 5 We share a commitment to making things better for clients and each other. We continually explore new technology and different ways of working to put our clients first. Bring your boldest ideas to our Research & Sustainable Investing Technology team and feel like you are making progress. About your team AMP Delivery is responsible for the design and delivery of all changes in business process and/or technology solutions that support the growth for Fidelity’s Global Investment Solutions & Services business. We partner with Investment Management, Asset Management Operations and Distribution teams across London, Hong Kong, Tokyo, Toronto, Australia, Singapore, and China.   The Research & Sustainability team delivers strategic initiatives that enhance investment decision-making through modern research workflows, investment data platforms, sustainability capabilities, advanced analytics, and AI-powered solutions. We are increasingly leveraging Large Language Models (LLMs), frontier AI models, and agentic workflows to transform how investment professionals discover insights, conduct research, and make investment decisions across Equities, Fixed Income, and Multi-Asset.  About your role This is a specialist, hands-on AI data engineering role within the AMP - Research & Sustainable Investing team. Reporting to the Data Engineering Lead, you will build the trusted data foundations that power machine learning, Large Language Model (LLM), retrieval-augmented generation (RAG), search and agentic AI workflows for investment research and sustainability use cases. You will engineer structured, semi-structured and unstructured data through the full AI data lifecycle - ingestion, transformation, enrichment, feature and evaluation dataset creation, embedding generation, vector indexing, retrieval and governed delivery. You will work primarily across Snowflake, AWS and Kafka while integrating with enterprise sources including Oracle and Microsoft SQL Server. You will work closely with AI/ML engineers, data engineers, research analysts, sustainability specialists and investment teams to make AI data accurate, discoverable, traceable, secure and production-ready. The role directly contributes to Accelerated Innovation, Cost Optimisation, Risk Mitigation and Business Enablement.

Design, build, test, deploy and operate production-grade data pipelines for structured, semi-structured and unstructured research, sustainability and investment data. Build AI-ready datasets for machine learning and generative AI, including feature, training and evaluation datasets, embeddings, vector indexes and retrieval-augmented generation workflows.                Engineer retrieval data flows that curate, enrich, index and serve trusted content for semantic search, vector search and LLM-based applications, with appropriate metadata and provenance. Help to develop metadata and knowledge structures, including taxonomies, ontologies, entity resolution and knowledge graphs where appropriate, to improve data discovery, retrieval and contextual understanding. Build reusable data services and APIs that expose governed investment data to AI/ML models, applications, analytics and agentic workflows. Apply data quality, lineage, data contracts, security, privacy, entitlements, auditability and provenance controls across data pipelines and AI-ready data products. Use Snowflake, AWS, Kafka and enterprise data platforms to ingest and prepare data, integrating safely with Oracle and Microsoft SQL Server where source or legacy data is required. Apply strong software and data engineering