Senior Data Engineering Consultant - Data bricks, SQL, etc

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

Primary Responsibilities:

• Contribute hands-on to the design, ETL development, and operation of cloud-native data pipelines on Azure and Databricks
• Design and optimize Spark-based ETL frameworks for large-scale batch and incremental processing
• Implement complex transformations and performance tuning using Python and Spark SQL
• Modernize on-prem ETL workloads to Databricks/snowflake, ensuring enterprise standards for scalability, reliability, and governance
• Collaborate with cross-functional teams to understand complex data requirements and deliver tailored solutions
• Ensure data quality and integrity by implementing robust data validation and monitoring processes
• Develop comprehensive documentation for data engineering processes and systems
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

• Bachelor's degree (B.E./B.Tech) in any engineering or related discipline
• Hands-on experience with Databricks and cloud-native data platforms, preferably on Azure
• Solid experience building ETL pipelines using Python, PySpark, and Spark SQL
• Experience with ETL tools (e.g., DataStage) and large-scale data warehouse implementations
• Experience migrating or modernizing on-prem ETL workloads to cloud architectures
• Solid knowledge on building AI solutions in Data pipelines
• Solid understanding of data warehousing concepts, including dimensional modeling, data quality, reconciliation, and performance tuning
• Proficient in SQL and working with relational and distributed database systems
• Familiarity with cloud ecosystems (Azure/AWS/GCP) and workflow orchestration tools such as Airflow
• Solid knowledge on building AI solutions
• Proven solid analytical and problem-solving skills with the ability to deliver scalable, reliable data solutions
• Demonstrated ability to lead a team

• Demonstrated ability to collaborate effectively across teams; leadership or mentoring experience