About the Opportunity

Title Senior Data Analytics Engineer I/II - Gen AI

Department ISS

Location Gurugram/Bangalore

Reports To Data Engineers - Lead

Level 5/6

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. So, bring your boldest ideas to our (name of team/business area) team and feel like you are making progress.

ISS Data Engineering Chapter is an engineering group comprised of three sub-chapters - Data Engineers, Data Platform and Data Visualisation - that supports the ISS Department.

Fidelity is embarking on several strategic programmes of work that will create a data platform to support the next evolutionary stage of our Investment Process. These programmes span across asset classes and include Portfolio and Risk Management, Fundamental and Quantitative Research and Trading.

This role is appropriate for a senior data engineer capable of taking ownership and a delivering a subsection of the wider data platform or data applications.

As a Senior Data Analytics Engineer with machine learning focus, you will transform our organization's analytics and AI capabilities by Driving AI Innovation, Enhancing Decision Intelligence, Establishing Technical Excellence, Enabling Business Transformation

Key Responsibilities

• Design and implement the data ingestion and indexing pipelines for unstructured content (docs, emails, PDFs, tickets) and structured sources (DBs, APIs, data products).
• Build and operate retrieval foundations: chunking/metadata strategies, embedding pipelines, indexing, hybrid search, ranking/re-ranking patterns, and retrieval diagnostics.
• Enable NLQ-to-data patterns for structured data (semantic layer, query generation/validation, guardrails, schema linking) and ensure safe execution.
• Define data quality + freshness controls: data validation, incremental updates, lineage, access controls, PII handling, and policy enforcement for AI usage.
• Provide platform-ready interfaces (APIs/SDKs/templates) so teams can adopt retrieval and data patterns consistently with minimal bespoke work.
• Instrument data/retrieval telemetry: coverage, hit-rate, latency, index health, drift signals, and cost drivers partner on incident/debug support for retrieval issues.

• Strong data engineering fundamentals: scalable pipelines, data modelling, batch/stream processing, and reliable operations.
• Applied retrieval expertise for LLMs: chunking/metadata design, embeddings/indexing, hybrid search, re-ranking, and retrieval evaluation/diagnostics.
• Experience integrating enterprise data sources securely (IAM/RBAC, data entitlements, PII controls, auditability).
• Practical understanding of LLM solution patterns (RAG/agent/NLQ) and the trade-offs that impact accuracy, latency, and cost.
• Ability to design reusable platform components (APIs/SDKs/templates), with strong documentation and enablement mindset.

• Education

• Master's or bachelor's degree in computer science, Data Science, Statistics, or related field
• Advanced certifications in machine learning, AI, or data science preferred

Feel rewarded

For starters, we'll offer you a comprehensive benefits package. We'll value your wellbeing and support your development. And we'll be as flexible as we can about where and when you work - finding a balance that works for all of us. It's all part of our commitment to making you feel motivated by the work you do and happy to be part of our team. For more about our work, our approach to dynamic working and how you could build your future here, visit careers.fidelityinternational.com.

For more about our work, our approach to dynamic working and how you could build your future here, visit careers.fidelityinternational.com.