Sr. Databricks Engineer

22 hours ago

Pune, Maharashtra, India Source-Right Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Position: Sr. Databricks Engineer / Azure Data Engineer (CBS410FT RM 3748)
**Note : Only local Pune candidates or those willing to relocate to Pune may apply

Interview Mode : L2 interviews will be conducted in person — apply only if open to face-to-face interviews
About The Role**
We are seeking a highly skilled Senior Databricks Engineer / Azure Data Engineer to design and implement high-performance, scalable, and secure data pipelines using Databricks, Spark, Delta Lake, and Azure Cloud. You will collaborate with data architects, scientists, and business stakeholders to transform raw data into actionable insights that drive business impact

Key Responsibilities
Data Pipeline Development

  • Build and optimize data pipelines using PySpark, Spark SQL, and Delta Lake.
  • Work across Databricks Workspace, Jobs, DLT, Repos, and Unity Catalog.
  • Implement Medallion (Lakehouse) architectures for scalable data solutions. Automation & Orchestration
  • Automate deployments via Azure DevOps / GitHub Actions.
  • Manage orchestration using ADF, Airflow, or Databricks Workflows. Governance & Quality
  • Ensure strong data governance, quality, and lineage across environments.

Essential
Required Skills & Qualifications

  • 5+ years of experience in Data Engineering (Databricks-focused).
  • Hands-on experience with PySpark, Delta Lake, and Azure.
  • Strong SQL and data modeling skills.
  • Experience with CI/CD and orchestration tools (ADF / Airflow / Databricks Workflows). Desirable
  • Experience working with healthcare or regulated data.
  • Knowledge of SQL Server, Synapse, and Power BI.
  • Azure or Databricks certifications.

Skills & Attributes

  • Strong analytical and problem-solving skills.
  • Collaborative and proactive team player.
  • Excellent communication and documentation skills.
  • Passion for data-driven innovation and transformation.

What We Offer

  • Opportunity to work on enterprise-scale data transformation projects.
  • Collaborative work environment with skilled professionals.
  • Competitive compensation and benefits.
  • Professional growth through continuous learning and upskilling.

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