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Azure Data Architect

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Lead Azure Data Engineer

A senior technical role is available for a Lead Data Engineer with hands-on expertise in Azure and Databricks.

The ideal candidate is responsible for designing, developing, and optimizing data pipelines using Azure and Databricks.

Key responsibilities include:

  • Designing, developing, and optimizing data pipelines using Azure and Databricks.
  • Hands-on work with Databricks Asset Bundles (DABs) for CI/CD and environment management.
  • Building and managing scalable ELT/ETL workflows with Databricks, Delta Lake, ADF, and other Azure services.
  • Continuously adopting and applying new Databricks features to accelerate delivery.
  • Optimizing Spark, SQL, and Python code for performance and scalability.
  • Applying software engineering best practices (e.g., TDD, CI/CD, modular design, code reviews) to ensure a robust, maintainable, and strategic data ecosystem.
  • Mentoring team members to improve overall team productivity and technical capability.
  • Delivering in a fast-paced environment with quick turnaround expectations.

Required skills and qualifications:

  • 8+ years in Data Engineering with at least 5 years hands-on in Azure & Databricks.
  • Strong expertise in:
  • Databricks (Delta Lake, Databricks SQL, Workflows, Databricks Asset Bundles, MLflow basics, unity catalog)
  • Azure Data Services (ADF, Azure Synapse, Azure Data Lake, Azure SQL)
  • Python, SQL, Spark (with proven performance optimization skills)
  • Strong knowledge of modern data architectures (Lakehouse, governance).
  • Track record of efficient delivery and helping teams accelerate execution.

Preferred skills:

  • Experience with AI-driven development tools to accelerate coding, improve productivity, and maintain high-quality implementations.
  • Exposure to Generative AI in Databricks (LLMOps, Model Serving, MosaicML, vector search).