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StoneXPosted 25 months ago

Lead - IT Data Engineering and Analytics

HybridBengaluru, Karnataka, India

Full TimeSenior LevelBachelors DegreeLarge

Job Summary

Own the architecture of the Azure data platform end-to-end, managing Databricks Lakehouse, Fabric, and the BI semantic layer. Lead delivery for a team of four engineers by breaking down work, unblocking, and mentoring while setting standards for data modeling, PySpark/SQL quality, and CI/CD. Engage directly with product, business, and technical stakeholders to identify and scope platform initiatives, partnering with Architecture, Security, and DevOps to meet enterprise standards. Define and uphold SLAs, lead incident response, and drive cost, performance, and reliability improvements. Architect AI platforms at scale using Azure AI Foundry and Databricks Mosaic AI. Hybrid work in Bangalore with travel as required.

Required Qualifications

  • 8+ years of data engineering / data platform experience, including 2–3 years as a technical lead owning architecture and guiding engineers
  • Deep, hands-on expertise in Azure Databricks — Delta Lake, PySpark, Unity Catalog, cluster and performance tuning at scale
  • Strong experience with Microsoft Fabric and ADLS Gen2
  • Strong Python (PySpark) and SQL; proficient in at least one additional language (Java, C#, or similar)
  • Hands-on with Docker, Git, Kubernetes, and IaC (Terraform, Ansible)
  • Solid competencies across Azure cloud networking, identity management, storage, and compute
  • Track record of architecture and design authority on non-trivial platforms
  • Bachelor's degree in Computer Science, Mathematics, Electrical Engineering, or related discipline — or equivalent experience

Desired Qualifications

  • Financial services or other regulated-industry experience
  • Production experience with Microsoft Fabric (OneLake, Direct Lake)
  • Data governance experience — Unity Catalog, lineage, data contracts, cost governance / FinOps on Databricks
  • Experience designing and operating BI solutions on Power BI and SSAS - dataset design, DAX, RLS, capacity and refresh
  • Familiarity with Kimball modeling patterns

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