Join Optum, a global leader in healthcare technology, dedicated to improving health outcomes for millions. As part of our innovative team, you'll contribute to advancing health optimization worldwide. We foster an inclusive culture with talented colleagues, comprehensive benefits, and ample career development. Be part of an organization that Cares, Connects, and Grows together.

Design and implement scalable data pipelines and ETL/ELT solutions using Azure Databricks, PySpark, and SQL. Migrate and modernize legacy data systems to Azure Databricks and Snowflake. Develop robust data ingestion, transformation, and quality frameworks for enterprise lakehouse architecture. Build reusable PySpark components for processing large healthcare datasets. Implement monitoring, logging, and automation for enhanced platform reliability. Collaborate with stakeholders to deliver high-quality data products and support data governance. Optimize Databricks environments and data pipelines for performance and cost.

Contribute to code reviews, technical design, and production support. Champion engineering best practices like CI/CD and automated testing. Explore and leverage AI-assisted engineering for improved delivery speed and quality.

A Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field is required. We seek candidates with over 3 years of experience in Data Engineering, ETL development, or Big Data platforms. Demonstrated expertise in Azure Databricks and PySpark development, along with hands-on experience in cloud data platforms like Azure Databricks, ADLS, and Snowflake is essential.

Proficiency in building large-scale batch and incremental data processing solutions is necessary. Experience with orchestration tools such as Airflow or ADF is required. Strong understanding of data quality validations, monitoring, and operational support processes is expected. Familiarity with Git and CI/CD practices is also important. Excellent analytical, problem-solving, and communication skills are critical for collaborating effectively within distributed teams.