Distinguished Data Engineer
Fidelity International (company site, opens in a new tab)BengaluruOn-siteDirect career pageEst. 40–65 LPA
Posted 10h ago
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Job description
Structured overview of role & requirements
About This Role
- Build and operate production-grade data pipelines and AI-ready datasets supporting machine learning, LLM, and generative AI workflows in investment research and sustainability domains.
- Engineer end-to-end AI data lifecycle including ingestion, transformation, embedding generation, vector indexing, and retrieval with Snowflake, AWS, Kafka, and enterprise data sources.
- Collaborate with AI/ML engineers and investment teams to ensure data accuracy, governance, provenance, security, and production readiness of AI data products.
Minimum Requirements
- Hands-on experience delivering production data engineering solutions for AI/ML use cases involving machine learning, LLMs, search, retrieval, and generative AI.
- Proficiency in Python, Spark, SQL, and experience with Snowflake, AWS, Kafka, Oracle, and Microsoft SQL Server integration.
- Understanding and application of data governance including data quality, lineage, access controls, privacy, and responsible AI controls.
- Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Experienced in designing, building, deploying, and maintaining secure, resilient, and traceable data pipelines and AI data components from design through production support.
- Skilled at translating AI and investment use cases into practical, governed data engineering solutions collaborating effectively with multidisciplinary teams.
- Comfortable applying strong problem-solving to ambiguous data and retrieval challenges with ownership of quality, security, and maintainability in complex enterprise environments.