Senior Data Engineer
Procter & Gamble (company site, opens in a new tab)5+ yrsHyderabadOn-siteDirect career pageEst. 18–28 LPA
Posted on 8 Sept
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Job description
Structured overview of role & requirements
About This Role
- Architect and lead AI-native data pipelines for ingestion, transformation, and serving optimized for analytics and AI consumption.
- Build and own the semantic data layer and KPI factory to provide standardized, trusted metrics for AI and business use.
- Govern data acquisition strategies and agent data access, ensuring auditability and responsible AI-human collaboration on Azure platform.
Minimum Requirements
- Bachelor’s Degree in related technical field or equivalent experience.
- At least 5+ years’ experience in Big Data solutions development using Spark and Databricks, with AI/ML or AI-assisted workflows experience.
- Proficient in Python (PySpark), SQL, and hands-on with vector databases, embedding pipelines, and RAG design.
- Experience with Azure Data Factory, Airflow, CI/CD pipelines, data lineage, auditability, and governance for AI data consumption.
Ideal Candidate Profile
- Experienced in designing Big Data architectures including Data Warehousing, Lakehouse, Data Mesh, and semantic layer design oriented towards AI/ML use cases.
- Skilled in integrating AI-native operating model concepts into data pipeline and access design, supporting safe AI-human workflows.
- Able to collaborate cross-functionally with engineering, governance, and business teams to deliver high-quality, audited, and explainable data infrastructure for AI applications.