Join Optum, a global leader in healthcare services, where technology drives our mission to help millions live healthier lives. As part of our team, you'll connect individuals with essential care, pharmacy benefits, data, and resources. We foster an inclusive culture, offering opportunities for growth, comprehensive benefits, and collaboration with talented peers. Advance global health optimization and make a tangible impact on the communities we serve.

UnitedHealth Group is dedicated to improving health and optimizing the healthcare system for everyone. We champion equity, addressing health disparities and striving for a world where all individuals can achieve their healthiest lives, regardless of background. Our commitment extends to environmental responsibility and delivering equitable care as a core enterprise priority.

As a Senior Data Engineering Lead, you will be responsible for ensuring compliance with employment contracts, company policies, and directives. This includes adaptability to changes in work location, teams, shifts, and benefits, reflecting the dynamic nature of our business. The company reserves the right to modify these policies at its discretion.

This role demands extensive expertise in data engineering with a focus on modern cloud technologies and big data platforms.

Key qualifications include: - Over 10 years of hands-on experience with Azure Databricks, Apache Spark, and Scala. - A minimum of 5 years working with Microsoft Azure. - Proven experience in designing and implementing data warehousing solutions and ETL processes. - Demonstrated ability in problem-solving, attention to detail, and strong communication and collaboration skills. - Deep understanding of Databricks architecture and capabilities. - Solid experience with cloud deployment platforms such as Azure and Kubernetes. - Proficiency with RDBMS, specifically Azure SQL Server. - Practical experience in DevOps, including CI/CD pipeline creation. - Experience in API development (REST or GraphQL). - In-depth knowledge of Scala, including functional programming and advanced language features. - Expertise in Apache Spark, optimizing jobs, and understanding its distributed model. - Familiarity with Java/J2EE or .NET is advantageous. - Strong grasp of distributed computing principles and big data processing concepts. - Knowledge of big data technologies like Hadoop, Hive, HDFS, and data lakes, with experience processing large datasets efficiently. - Advanced SQL querying skills and experience with relational databases. - Proven ability to integrate and leverage AI tools such as Github Copilot, M365 Copilot, StoryCraft, and GenAI in development workflows.