Data Engineer — Source Integrations & Pipelines

Location: Pune, India

Department: Technology & Innovation

Experience: 7+

Skills: Broad source integration, Data quality, testing, pipeline observability, Azure data services, OT/IoT exposure, Snowflake production experience, Object/file storage — MinIO/NFS

• Build and operate end-to-end data pipelines from source systems into the lakehouse / data fabric.
• Integrate structured, semi-structured, document, and time-series sources into a common platform.
• Implement data processing, cleansing, and transformation for the priority pilot use cases.
• Ensure pipeline reliability, monitoring, and data quality across all feeds.
• Work with the architect to align pipelines to platform standards and modeling conventions.
• Prepare curated datasets for the visualization and MLOps workstreams.

• Strong data engineering background building production pipelines end to end.
• Hands-on experience with Azure data services and readiness to work with Snowflake.
• Experience integrating diverse sources: Oracle ERP, MongoDB, PostgreSQL, Cassandra, Redis, InfluxDB, and time-series data.
• Solid data processing skills (batch and streaming) and strong SQL.
• Experience with object and file storage such as MinIO / NFS.
• Data quality, testing, and pipeline observability practices.

• Snowflake production experience.
• Exposure to OT / IoT data feeds.
• Familiarity with orchestration frameworks and infrastructure-as-code.

• 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.