Principal Data Engineer - Remote

Requisition Number: 2400247

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 in making healthcare work better for everyone through people-led, responsible AI while Caring. Connecting. Growing together.

As a Principal Data Engineer within the Optum Insight Engineering AI team, you will design and develop robust public cloud data systems, services, and reusable patterns that drive massive scale and performance. Our team's vision is to deliver secure, private, and highly scalable Azure cloud solutions that enable the organization to utilize clean, reliable data safely and swiftly. In this role, you will lead the creation of modern ETL/ELT pipelines, Spark workflows, and AI integrations. Working with advanced platforms such as Azure Databricks, Snowflake, and LLMs, you will build data solutions that empower machine learning, insights generation, and business automation, directly contributing to better clinical and administrative connectivity across the healthcare system.

You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. The individual in this role must work in central time zone hours.

Primary

Responsibilities

• Design and Develop Scalable Cloud Applications: Develop services, controls, and reusable patterns (such as microservices and Azure functions) that enable the team to deliver value safely, quickly, and sustainably in the Azure public cloud while enabling security and privacy at scale
• Build and Optimize Large-Scale Data Pipelines: Design, build, optimize, and manage modern large-scale data pipelines and ETL/ELT processing on Azure Databricks, LakeBase, and Apache Spark to support data integration, analytics, machine learning features, and predictive modeling
• Deploy AI and Data-Driven Solutions: Develop and deploy large-scale data pipelines empowering machine learning algorithms, insights generation, business intelligence dashboards, reporting, and new data products while utilizing enterprise-approved AI tools to address complex business challenges
• Develop AI-Powered Business Solutions: Build AI-based solutions for solving business needs, automating processes, and streamlining workflows to drive operational efficiency and continuous improvement
• Architectural Evolution and Standards: Participate in the architectural evolution of data engineering patterns, frameworks, systems, and platforms, including defining best practices and standards for managing data collections and integrations
• Improve System Quality and Data Reliability: Write advanced, complex SQL with performance tuning and optimization to identify and implement ways to improve data reliability, data integrity, system efficiency, and overall quality
• Collaborative Leadership and Mentoring: Foster high-performance, collaborative technical work resulting in high-quality output. Mentor other data engineers, providing technical direction and training on leveraging cloud data platforms
• Stakeholder and Requirement Analysis: Intersect skillfully with business stakeholders and third-party technical organizations to understand new product capabilities, decompose implementations into specific functional changes, analyze data for decision-making, and provide detailed, realistic estimates
• Evaluate Emerging Trends: Evaluate emerging trends to inform solution design, strategic innovation, and the evolution of cloud data architectures
• Best Practices in performance scalability and optimization

You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Required

Qualifications

• 8+ years of software or data engineering experience, with strong expertise in data integration, data modeling, data architecture, and ETL/ELT
• 5+ years of hands-on development experience using Python
• 4+ years of experience with Apache Spark/PySpark and distributed data processing
• 5+ years of advanced SQL experience, including data modeling, complex queries, and performance optimization
• 1+ years of experience designing and integrating REST, GraphQL, or similar APIs
• 1+ years of experience integrating LLMs, AI agents, or generative AI capabilities into engineering workflows or enterprise applications
• 1+ years of experience building data solutions using Azure Databricks, Snowflake, or comparable cloud data platforms
• 1+ years of experience using modern software engineering practices including Git, CI/CD, automated testing, code quality, and infrastructure as code
• 1+ years of experience designing scalable, maintainable data platforms and services and troubleshooting complex production/data-processing issues

Preferred Qualifications

• Experience with Azure Databricks, Unity Catalog, Azure Functions, Azure Service Bus, and/or Snowflake
• Experience with Terraform and GitHub Actions
• Experience with spec-driven development and AI-assisted software engineering
• Proven ability to work across data, API, and application layers and understand end-to-end system dependencies
• Proven solid problem-solving skills and ability to quickly learn unfamiliar platforms and technologies

All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy

Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your sala