Overview:
Lead the technical direction of StoneX's Azure data platform. You will own the platform architecture of our Lakehouse and BI semantic layer, guide a team of four engineers, and work directly with product, business, and technical stakeholders to deliver platform initiatives. This is a hands-on technical lead role — you set direction, review designs, and solve the hardest problems.
Responsibilities:
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Own the architecture of the Azure data platform end-to-end — Databricks Lakehouse, Fabric, and the BI semantic layer (Power BI, SSAS/AAS).
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Engage directly with product, business, and technical stakeholders to identify, scope, and deliver data platform initiatives.
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Lead delivery across a team of four engineers — break down work, unblock, mentor, and raise the engineering bar through design and code reviews.
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Set standards for data modeling, PySpark/SQL quality, semantic-model design, testing, CI/CD, and production readiness.
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Own platform infrastructure as code (Terraform, Kubernetes, Helm) and the CI/CD, monitoring, and observability that supports it.
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Define and uphold SLAs for the platform; lead incident response; drive cost, performance, and reliability improvements.
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Partner with Architecture, Security, DevOps, Cloud Engineering, and Networks to meet enterprise and regulatory standards.
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Architecting AI platforms at scale — Claude, GitHub, Azure AI Foundry, and Databricks Mosaic AI
Qualifications:
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8+ years of data engineering / data platform experience, including 2–3 years as a technical lead owning architecture and guiding engineers.
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Deep, hands-on expertise in Azure Databricks — Delta Lake, PySpark, Unity Catalog, cluster and performance tuning at scale.
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Strong experience with Microsoft Fabric and ADLS Gen2.
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Strong Python (PySpark) and SQL; proficient in at least one additional language (Java, C#, or similar).
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Hands-on with Docker, Git, Kubernetes, and IaC (Terraform, Ansible).
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Solid competencies across Azure cloud networking, identity management, storage, and compute.
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Track record of architecture and design authority on non-trivial platforms.
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Bachelor’s degree in Computer Science, Mathematics, Electrical Engineering, or related discipline — or equivalent experience.
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Financial services or other regulated-industry experience.
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Production experience with Microsoft Fabric (OneLake, Direct Lake).
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Data governance experience — Unity Catalog, lineage, data contracts, cost governance / FinOps on Databricks.
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Experience designing and operating BI solutions on Power BI and SSAS - dataset design, DAX, RLS, capacity and refresh.
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Familiarity with Kimball modeling patterns.
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Hybrid, Bangalore (4 days).
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Dynamic, time-sensitive environment.
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Travel as required.
