About Position:
We are seeking a skilled Azure Databricks Engineer with 6–8 years of experience in Python and Py Spark to join our data engineering team. This role focuses on building and optimizing scalable data pipelines and ETL workflows using Azure Databricks and modern data technologies. The ideal candidate will work closely with cross-functional teams to design and deliver high-performance, reliable, and data-driven solutions, while ensuring data quality, efficiency, and scalability within the Azure ecosystem.
Role: Azure Databricks Engineer
Location: Bangalore, Pune & Chennai
Experience: 6 to 8 Years
Job Type: Full Time Employment
What You'll Do:
Design and develop scalable data pipelines using Azure Databricks and Py Spark
Build and maintain ETL workflows for processing large datasets
Write optimized Python and SQL code for data transformation and analysis
Integrate Databricks with Azure services (ADLS, ADF, Synapse)
Perform performance tuning of Spark jobs (partitioning, caching, optimization techniques)
Ensure data quality, integrity, and governance across pipelines




Collaborate with business and technical stakeholders for requirement gathering and solution design
Troubleshoot and resolve data pipeline and performance issues
Expertise You'll Bring:
Hands-on experience with Azure Databricks
Strong proficiency in Python and Py Spark
Good knowledge of SQL and data transformation techniques
Experience with Azure Data Lake (ADLS), Azure Data Factory (ADF), Synapse
Understanding of ETL processes and data warehousing concepts
Familiarity with Delta Lake and Spark optimization techniques
Experience with version control tools (Git)
Benefits:
Competitive salary and benefits package
Culture focused on talent development with quarterly growth opportunities and company-sponsored higher education and certifications
Chance to work with cutting-edge technologies
Employee engagement initiatives such as project parties, flexible work hours, and Long Service awards
Annua

📌 Azure databricks engineer (Pune)
🏢 Persistent Systems
📍 Pune