Data Platform Architect (Data Fabric / Lakehouse)

Location: Pune, India

Department: Technology & Innovation

Experience: 12+ years overall, with 4+ years architecting data platforms (lakehouse / data fabric).

Skills: MLOps platform requirements familiarity, Snowflake, Agentic AI / advanced analytics roadmap, Lakehouse/data fabric architecture, Azure data stack

• Design the target data fabric / lakehouse architecture on Azure, with a clear migration path to Snowflake.
• Define ingestion, storage, processing, governance, and consumption layers, including how GraphDB fits for asset topology and ontology.
• Validate the architecture against one to two priority pilot use cases before broad rollout.
• Set data modeling, security, lineage, and access-control standards across all sources.
• Establish the reference patterns for IT / OT / IoT integration and hand them to the integration engineers.
• Review designs from data engineering, GraphDB, and MLOps workstreams for consistency with the platform blueprint.
• Plan the phased roadmap so agentic AI capabilities can be layered on once the data foundation is stable.

• Proven experience architecting data lakehouse or data fabric platforms end to end.
• Deep hands-on Azure data stack experience (Data Lake, Synapse / Fabric, Data Factory, or equivalent).
• Snowflake architecture and migration experience.
• Strong data modeling across relational, document, time-series, and graph paradigms.
• Experience integrating heterogeneous IT / OT / IoT sources at enterprise scale.
• Working knowledge of GraphDB / knowledge graph concepts for topology and ontology.
• Governance, lineage, and audit-trail design experience.

• Exposure to intelligent building management or industrial OT environments.
• Familiarity with MLOps platform requirements.
• Experience planning for agentic AI or advanced analytics on top of a data platform.

• Proactive and self-driven, able to take ownership and move work forward without waiting to be told.
• AI-enabled in day-to-day work, comfortable using AI tools and copilots to accelerate delivery and quality.
• Strong self-learner who stays current with evolving tools, platforms, and practices.
• Good team player who collaborates well across engineering, operations, and stakeholder groups.