Data Engineering Lead-Azure Data bricks, SQl,Python,Spark,Airflow
Optum (company site, opens in a new tab)4+ yrsBengaluruOn-siteDirect career pageEst. 20–35 LPA
Posted 12h ago
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, test, and deploy scalable data pipelines using Azure Databricks, Spark SQL, Python, and Airflow.
- Build and maintain data ingestion, transformation, and curation processes across multiple enterprise data sources with attention to performance and scalability.
- Support data platform modernization, cloud migration, CI/CD processes, production deployments, incident resolution, and collaborate with cross-functional teams on analytics and operational needs.
Minimum Requirements
- Bachelor's Degree in Engineering, Computer Science, Information Technology, MCA, or equivalent experience.
- 4+ years of relevant hands-on experience in Azure Databricks and modern data engineering.
- Proven technical skills in Azure Databricks, Apache Spark, Spark SQL, SQL Development, Python programming, Apache Airflow, Delta Lake, and Azure Data Lake Storage (ADLS).
- Experience working in Agile/Scrum delivery environments.
Ideal Candidate Profile
- Experienced data engineer with deep expertise in Azure cloud data platforms, especially Azure Databricks and associated tools like Airflow and Delta Lake.
- Skilled in building and optimizing enterprise-scale data pipelines supporting analytics and data modernization initiatives.
- Ability to work independently on complex technical solutions, troubleshoot data issues, and collaborate effectively with stakeholders in a fast-paced environment.