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:
- Design and Build Data Infrastructure: Develop and maintain scalable data pipelines (ETL/ELT) for large-scale data processing
- Data Architecture: Lead architectural decisions for data warehousing and big data solutions
- Optimize Performance: Improve database performance, query efficiency, and data workflows
- Data Quality and Governance: Implement frameworks for data validation, monitoring, and compliance
- Collaboration: Work with data scientists, analysts, and business teams to enable analytics and machine learning
- Mentorship: Guide junior engineers and promote best practices in data engineering
- Automation and Deployment: Create automated testing and deployment processes for data systems
- Troubleshooting: Resolve complex data issues and ensure system reliability
- 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
Required Qualifications:
- Undergraduate degree or equivalent experience
- 7+ years of experience in Spark/Scala, Azure Databricks, Azure Data Factory, Airflow and Kafka. Proficient in coding, testing, implementing, debugging, and documenting the complex Spark Jobs
- Programming: Solid in Azure Databricks, Python/Scala, SQL experience
- ETL Tools and Big Data: Hands-on experience with Spark, Hadoop, or similar frameworks
- Cloud Platforms: Azure, (or GCP) experience
- Containerization and Orchestration: Docker, Kubernetes
- Data Modeling and Warehousing: Expertise in relational and NoSQL databases
- Distributed Systems: Knowledge of data partitioning and parallel processing
- Data Security and Compliance: Familiarity with GDPR, HIPAA, or similar standards
Preferred Qualifications:
- Experience with Snowflake
- Streaming Technologies: Kafka or similar message queuing systems
- AI and Machine Learning Deployment: implementing AI solutions (RAG development, Agents creation), Exposure to ML model integration
- CI/CD for Data: Jenkins or other DevOps tools for data workflows
- BI Tools: Tableau, Power BI for reporting
