Senior Data Engineer

Job Location HYDERABAD OFFICE INDIA PSC PGH Job Description P&G was founded over 180 years ago as a simple soap and candle company. Today, we're the world’s largest consumer goods company and home to iconic, trusted brands that make life a little bit easier in small but meaningful ways. We've spanned three centuries thanks to three simple ideas: leadership, innovation and citizenship. The insight, innovation and passion of hardworking teams have helped us grow into a global company that is governed responsibly and ethically, that is open and visible, and that supports good causes and protects the environment. This is a place where you can be proud to work and do something that matters. Dedication from Us: You'll be at the core of breakthrough innovations, be given exciting assignments, lead initiatives, and take ownership and responsibility, in creative workspaces where new insights thrive. All the while, you'll receive outstanding training to help you become a leader in your field. It is not just about what you'll do, but how you'll feel: encouraged, valued, purposeful, challenged, heard, and inspired.

Continuous mentorship – you will collaborate with peers and receive both formal training as well as day-to-day mentoring from your manager dynamic and encouraging work environment– employees are at the centre, we value every individual and support initiative, promoting agility and work/life balance.

We’re looking for a Senior Data Engineer to join our Supply Chain Innovation team and build the trusted data foundation for an AI-native operating model where people and AI work together to improve decisions, execution, and business outcomes. This role goes beyond moving and transforming data for dashboards and reports: you will architect pipelines that feed knowledge, action, and cognitive agents with trusted, realtime, and governed data, and design the semantic layer, KPI logic, and data acquisition strategy as first-class engineering concerns rather than afterthoughts. You will leverage modern Agile and DevOps practices to lead the design and development of AI-native data systems, delivering projects in multinational teams.

Responsibilities Architect AI-native data pipelines — design end-to-end ingestion, transformation, and serving pipelines optimized for both traditional analytics consumption and agentic consumption (retrieval-augmented generation, tool-calling, MCP-based access). Build the semantic data layer — standardize and contextualize data (schemas, metadata, business definitions) so knowledge and cognitive agents can reliably interpret and reason over it. Own the KPI factory / manipulation layer — encode standard KPI calculations and business logic in reusable back-end services so agents and downstream consumers retrieve trusted outputs instead of recalculating in real time. Design the data acquisition strategy — define systems of record, reference data, access rules, refresh frequency, and ownership for every data element feeding AI agents. Build agent retrieval infrastructure — implement vector stores, embedding pipelines, and RAG patterns that support knowledge agents at production scale. Govern agent data access — Design permissioning, guardrails, approval workflows, and audit logging for AI-assisted and automated data interactions, ensuring appropriate human accountability for sensitive or consequential actions. Lead the full application lifecycle — from development, deployment, and upgrade through replacement or termination, for AI-native data pipeline components on Azure. Enforce engineering standards — CI/CD, testing, data quality checks, drift detection, and evaluation of agent-facing outputs, in line with modern DevOps and Agile practices. Collaborate cross-functionally — partner with agentic engineers, platform engineers, governance and risk leads, and business process experts to translate work-process redesign into production-grade data