Data Architect

Skills And Expertise

• Hands-on experience building modern data platforms on Azure using tools and services such as: Azure Databricks, Azure Data Factory, ADLS Gen2, SQL Database, Microsoft Fabric, Event Hub, Stream Analytics, Cosmos DB, Azure Purview, Log Analytics, and Azure Data Explorer.
• Deep expertise in the Databricks ecosystem, including: PySpark, Notebooks, Unity Catalog, Delta Live Tables, Workflows, SQL Warehouse, Mosaic AI, AI/BI Genie.
• Experience of designing and developing metadata-driven frameworks (relevant for Data Engineering processes).
• Strong programming, debugging, and performance tuning skills in Python and SQL.
• Experience with Agentic AI-assisted engineering using tools like Claude Code, Gemini Code, Codex, Copilot, etc., including effective use of Claude Skills, CLAUDE.md / AGENTS.md, MCP tools, hooks and repo-level coding workflows.
• Ability to design, guide, and review AI-generated code responsibly, including prompt/task decomposition, context engineering, tool configuration, guardrails, testing, debugging, and production-quality code validation.
• Good Experience of Data modeling (both Dimensional and 3-NF)
• Good Exposure to developing LLM/GenAI-powered applications.
• Sound understanding of CI/CD processes using Git and Jenkins or Azure DevOps.
• Familiarity with big data platforms such as Cloudera (CDH) or Hortonworks (HDP) is a plus.
• Exposure to technologies like Neo4j, Elasticsearch, and vector databases is desirable.
• Bonus: Experience with Azure infrastructure provisioning, networking, security, and governance.