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Job Description
Structured overview of role & requirementsAbout This Role
Own the design, build, governance, and operational readiness of AI data engineering pipelines and data products to support AI-enabled products ensuring trusted, permissioned, explainable, and reusable data.
Define and deliver governed data products across multiple domains with ownership, SLAs, and quality controls, while partnering with data stewards and cross-functional teams.
Implement data quality, metadata, security/privacy controls, and monitor AI data lifecycle operations to ensure pipeline reliability, freshness, and compliance with regulatory requirements.
Minimum Requirements
Work Experience Required: Not explicitly mentioned in the JD
Strong expertise in data engineering including pipeline engineering, orchestration (ETL/ELT, API/event integration), data product development, quality rule design, metadata/cataloging, access control, and cloud data platforms.
Experience or knowledge in AI data engineering concepts such as RAG data preparation, document ingestion, chunking, embeddings, vector stores, semantic retrieval, and AI data observability.
Location Requirements: Hybrid work mode based in Bangalore; Shift timing: 11:00 AM - 8:00 PM.
Ideal Candidate Profile
Experienced in translating AI product and business needs into scalable, governed data engineering solutions with emphasis on trust, security, and reusability.
Able to navigate complex collaboration across product, AI, architecture, security, risk, and governance functions with strong data stewardship mindset.
Skilled at solving problems with incomplete or conflicting data and making strategic decisions on centralization vs federation vs reuse of data capabilities.