Senior Data Engineer
About The Position
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. You will enjoy the flexibility to telecommute from anywhere within the U.S. as you take on some tough challenges.
Requirements
- Bachelor’s degree
- 8+ years of experience in each of the following: Azure Databricks, Azure Data Lake Storage (ADLS), Apache Spark (Core concepts and performance tuning), Scala, SQL
Nice To Haves
- Healthcare domain experience (claims, clinical, eligibility, provider, member, HIPAA-aware handling preferred)
- Data Streaming (e.g., Spark Structured Streaming and streaming design patterns)
- Python/PySpark
- Azure (general platform knowledge)
- MongoDB
- Excellent problem-solving skills and attention to detail
- Strong communication and collaboration skills
Responsibilities
- Design and develop Azure cloud-native enterprise data solutions with emphasis on data integration, transformation, and governance
- Build solution designs and technical designs for data pipelines based on business and technical requirements
- Develop and standardize reusable plug-and-play components that can be orchestrated into: data ingestion patterns (batch/streaming), data flows across multiple zones (raw/curated/consumption as applicable), data quality frameworks and validation rules
- Implement and maintain pipelines leveraging Databricks + ADLS, ensuring reliability, scalability, and maintainability
- Identify opportunities to enhance/streamline existing codebase for: automation, performance improvements, scalability and reliability, operational efficiency and reduced run-cost
- Support backlog execution by helping prioritize pipeline development, estimate effort, and create implementation roadmaps
- Lead a team of data engineers by providing technical direction, code reviews, and design guidance
- Provide QA, UAT, and implementation support, including deployment readiness, operational handoffs, and production troubleshooting
- Ensure adherence to engineering standards (documentation, logging/monitoring expectations, and CI/CD practices where applicable)
- Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI.
Benefits
- comprehensive benefits package
- incentive and recognition programs
- equity stock purchase
- 401k contribution
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What This Job Offers
Job Type
Full-time
Career Level
Senior
