Data Engineer - ETL, SQL, Databricks
Optum (company site, opens in a new tab)HyderabadOn-siteDirect career pageEst. 12–25 LPA
Posted 1d ago
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, and operate cloud-native ETL data pipelines on Azure and Databricks focusing on scalable batch and incremental processing.
- Modernize on-premises ETL workloads to cloud platforms such as Databricks and Snowflake ensuring enterprise standards for scalability, reliability, and governance.
- Collaborate with cross-functional teams to deliver tailored data engineering solutions, including enforcing data quality, validation, and monitoring.
Minimum Requirements
- Bachelor's degree (B.E./B.Tech) in engineering or related discipline.
- Hands-on experience with Databricks and cloud native data platforms, preferably Azure.
- Experience with ETL tools (e.g., DataStage) and migrating on-prem ETL workloads to cloud.
- Proficient in Python, PySpark, Spark SQL, and SQL with practical knowledge of data warehousing concepts and cloud ecosystem tools like Airflow.
Ideal Candidate Profile
- Experienced in designing and optimizing Spark-based ETL frameworks at scale, with a strong understanding of dimensional modeling and data quality.
- Comfortable working in complex, cross-functional environments requiring collaboration and delivering production data solutions.
- Ability to handle performance tuning, data validation, and documentation in cloud-based data engineering roles, with leadership or mentoring experience considered advantageous.