Join Optum, a global leader in health optimization, and contribute to improving millions of lives through innovative technology. We foster an inclusive culture with talented peers, comprehensive benefits, and robust career development. Advance health optimization on a global scale by Caring, Connecting, and Growing together.

This Senior Data Engineering Consultant role is pivotal in shaping enterprise data solutions that directly impact health outcomes. You will be instrumental in connecting people with the care, pharmacy benefits, data, and resources they need for healthier lives. This position offers a unique opportunity to make a significant impact on the communities we serve and drive the future of health optimization.

Lead the complete data engineering lifecycle, from architecture and design to development, deployment, and ongoing optimization of enterprise data solutions. Drive technical strategy and provide leadership for significant data modernization and cloud transformation projects. Design scalable, secure, and high-performing data platforms utilizing Azure cloud services and modern data architectures.

Manage data acquisition and integration from diverse sources for enterprise analytics, reporting, AI, and operational needs. Establish robust ETL/ELT frameworks and architecture standards to enhance scalability and maintainability. Provide technical guidance and mentorship, conduct reviews, and enforce engineering best practices. Lead initiatives in data quality, governance, lineage, and metadata management. Partner with stakeholders to translate business requirements into effective data solutions and define modern Lakehouse, Data Warehouse, and Data Mesh architectures.

A Bachelor's Degree in a relevant technical field is required, alongside 8+ years of comprehensive experience in Data Engineering, Data Warehousing, and Data Integration. Expertise in Microsoft Azure, including Azure Data Factory, Databricks, ADLS Gen2, and Synapse Analytics, is essential, with 5+ years of hands-on experience.

Demonstrate 5+ years of experience building large-scale ETL/ELT solutions using technologies like Spark, Python, Scala, and SQL. Proven ability in designing enterprise data architectures for relational and non-relational platforms, managing distributed data processing frameworks like Apache Spark, and leading technical teams with 3+ years of experience. Familiarity with healthcare data and analytics platforms is highly advantageous. Experience in designing cloud-native Lakehouse and Data Warehouse architectures, implementing CI/CD pipelines, and delivering platform modernization initiatives is also expected.