Senior Azure Data Architect

20 hours ago

Bikaner, Rajasthan, India beBeeData Full time ₹ 22,50,000 - ₹ 25,80,000

Job Title: Lead Data Engineer

Work Description:

  • A highly motivated and experienced Lead Data Engineer is required to join a growing team.
  • The successful candidate will design, develop, and optimize data pipelines using Azure and Databricks.
  • Strong expertise in Databricks, Azure Data Services, Python, SQL, Spark, and modern data architectures is required.

Key Responsibilities:

  1. Design, develop, and optimize data pipelines using Azure and Databricks.
  2. Hands-on work with Databricks Asset Bundles for CI/CD and environment management.
  3. Build and manage scalable ELT/ETL workflows with Databricks, Delta Lake, ADF, and other Azure services.
  4. Continuously adopt and apply new Databricks features to accelerate delivery.
  5. Optimize Spark, SQL, and Python code for performance and scalability.
  6. Apply software engineering best practices to ensure a robust, maintainable, and strategic data ecosystem.
  7. Mentor team members to improve overall team productivity and technical capability.

Required Skills & Qualifications:

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

Soft Skills & Attributes:

  • Efficiency-driven mindset – focused on speeding up both personal and team delivery.
  • Strong communicator within the team, able to share knowledge and mentor effectively.
  • Highly motivated, proactive, and results-oriented.
  • Ability to work in a fast-paced environment with quick turnarounds.

Preferred Skills:

  • Experience with AI-driven development tools to accelerate coding and improve productivity.
  • Exposure to Generative AI in Databricks.

Work Hours:

  • Must have 5–6 hours daily overlap with USA team (EST time zone) for collaboration.

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