getSummary
Written in English from the original postingSenior Databricks Data Engineer role in Bengaluru, India, focused on building and optimizing scalable data pipelines using Azure Databricks. The role covers ETL/ELT, Delta Lake, Unity Catalog, orchestration, data quality, security, monitoring, and CI/CD for Databricks deployments. The posting requires proficiency in PySpark, SQL, and Python and mentions 8 years of data engineering experience.
Job description
Interview - Face to face
Position Overview:
Build and maintain scalable data pipelines using Azure Databricks to support DATA & AI ACDP projects. Apply 3-4 years of experience to deliver reliable ETL processes and collaborate on data-driven insights.
Key Responsibilities:
- Design, build, and optimize data pipelines in Azure Databricks for ingestion, ETL/ELT, and transformations, implementing Medallion Architecture (Bronze, Silver, Gold) with Delta Lake for data quality and versioning.
- Utilize Databricks Spark (PySpark, SQL), Delta Live Tables, and Unity Catalog for pipeline development, governance, and basic streaming.
- Integrate data from ADLS Gen2, Azure SQL Database, and SQL Pools; support orchestration via Databricks workflows.
- Implement CI/CD in Azure DevOps for Databricks deployments, including Bicep templates and ADF integration.
- Apply data quality measures (expectations, constraints), security (RBAC, encryption), and monitoring for performance/cost efficiency using auto-scaling and Photon.
- Work with analysts and stakeholders to refine requirements into functional workflows; handle data cleansing, modeling, and Python/SQL scripting for structured/unstructured data.
- Troubleshoot pipelines and contribute to documentation/best practices.
Required Qualifications:
- 8 years in data engineering, focused on Azure Databricks pipelines and ETL
- Proficiency in PySpark, SQL, Python; experience with cloud storage and basic orchestration
- Familiarity with Azure fundamentals and collaborative tools