Sr Data Engineer

Role Description

The Optum Clinical Platform (OCM) is a top five initiative aimed at providing a single medical management platform. OCM will enable clinical programs to meet their specific business needs while maintaining consistent case and individual health data across the continuum of care services across our enterprise.

Our end-goal is to better nurture a lifelong relationship with our patients, members, clinicians, and partners to achieve the best health outcomes and lowest healthcare costs by connecting patients and providers simply and seamlessly across touchpoints of care. We will achieve this by:

• Developing a clinical platform that enables reusability, improves speed to market, and reduces redundancy of systems across the enterprise to achieve cost containment.
• Leveraging our platform offerings by allowing lines of business to select from existing products already built, allowing every line of business to seamlessly stitch together solutions to meet their custom end-to-end needs in a faster and cost-efficient manner.
• Fostering collaboration by encouraging a federated model, allowing lines of business to build in a low code/no code environment, creating a simple way to turn business goals into reality.

Primary Responsibility:

• Design, build, and operate scalable ETL/ELT pipelines for structured and semi‑structured data across internal and external sources.
• Develop cloud‑native data solutions on modern data platforms (e.g., Databricks lakehouse, Snowflake).
• Apply data modeling, transformations, and enrichment to produce trusted, analytics‑ready datasets.
• Ensure data quality, reliability, and auditability through validation, reconciliation, and monitoring.
• Implement and follow enterprise data governance, security, and compliance standards.
• Optimize data workloads for performance, cost efficiency, and operational reliability.
• Support modernization efforts, including migration of legacy ETL pipelines to cloud‑native architectures.
• Partner with product, analytics, and business stakeholders to translate requirements into production‑grade data solutions.
• Enable downstream analytics, reporting, and AI/ML workloads through well‑designed data assets.
• Apply software engineering best practices, including CI/CD, version control, testing, and code reviews.
• Contribute to architectural discussions and mentor junior engineers.
• Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI.

Qualifications

• Bachelor's degree in Computer Science, Engineering or related field.
• 5+ years of experience as a Data Engineer or in data platform/analytics engineering roles.
• 3+ years of experience with SQL, data modeling, and data transformations.
• 3+ years of hands‑on experience with Databricks and/or Snowflake and large‑scale data processing.
• 3+ years of experience building ETL/ELT pipelines, data warehouses, and analytical data stores.
• 3+ years of experience with source control and DevOps practices (Azure DevOps, GitHub, CI/CD).

Requirements

• Experience building enterprise-scale data platforms.
• Strong skills in performance tuning and debugging large-scale pipelines.
• Experience with real-time/streaming frameworks (Structured Streaming).
• Ability to work in distributed, cross-functional global teams.
• Exposure to GenAI tools (e.g., GitHub Copilot) for engineering productivity.
• Strong understanding of secure coding practices and vulnerability remediation.
• Proven ability to analyze logs, troubleshoot production issues, and optimize performance.
• Demonstrated capability to design and deploy AI-powered solutions responsibly.

Benefits

• Comprehensive benefits package.
• Incentive and recognition programs.
• Equity stock purchase.
• 401k contribution (all benefits are subject to eligibility requirements).