Role Description
Lead I - Data Engineering
Who We Are
At UST, we help the world’s best organizations grow and succeed through transformation. Bringing together the right talent, tools, and ideas, we work with our client to co-create lasting change. Together, with over 30,000 employees in 30+ countries, we build for boundless impact—touching billions of lives in the process. Visit us at .
Job Description
Design, build, and optimize data pipelines and ETL/ELT workflows using Databricks and Apache Spark (PySpark).
Develop scalable, high performance data solutions using Spark distributed processing.
Lead engineering initiatives focused on automation, performance tuning, and platform modernization.
Implement and manage CI/CD pipelines using Git-based workflows and tools such as GitHub Actions or Jenkins.
Collaborate with cross-functional teams to translate business needs into technical solutions.
Ensure data quality, governance, and security across all processes.
Troubleshoot and optimize Spark jobs, Databricks clusters, and workflows.
Participate in code reviews and develop reusable engineering frameworks.
Should have knowledge of utilizing AI tools to improve productivity and support daily engineering activities.
Strong knowledge and hands-on experience in Databricks Genie, including prompt engineering, workspace usage, and automation. Required Skills & Experience:
5+ years of experience in Data Engineering or related fields.
Strong hands-on expertise in Databricks (notebooks, Delta Lake, job orchestration).
Deep knowledge of Apache Spark (PySpark, Spark SQL, optimization techniques).
Strong proficiency in Python for data processing, automation, and framework development.
Strong proficiency in SQL, including complex queries, performance tuning, and analytical functions.
Solid knowledge of Databricks Genie and leveraging it for engineering workflows.
Strong experience with CI/CD and Git-based development workflows.
Proficiency in data modeling and ETL/ELT pipeline
📌 Databricks Developer (Bengaluru)
🏢 UST
📍 Bengaluru