Principal Data Engineer

Optum; United States; Hybrid; USD 140,000 - 210,000; Full time

Job summary

Optum is seeking a Principal Data Engineer to design and develop scalable cloud data systems in Azure, enabling secure data access and AI-enabled insights. You will lead ETL/ELT pipelines, Spark workflows, and modern data platforms to support ML, analytics, and automation across healthcare data ecosystems.

The role is remote within the United States with CST hours; some offices in DC/Minneapolis may require in-person days.

Qualifications

• Bachelor’s degree or equivalent experience
• 10+ years of experience in data engineering, data integration, data modeling

Responsibilities

• Design and develop scalable cloud data systems in Azure
• Build and optimize large-scale data pipelines using Azure Databricks, Snowflake, and Spark
• Deploy AI-enabled data products, dashboards, and BI reporting
• Mentor and lead data engineers, providing technical direction
• Collaborate with stakeholders to translate requirements into data solutions
• Ensure data quality, security, and privacy at scale
• Evaluate emerging trends to inform architecture and tooling
• Define standards for data collections, integrations, and governance

Education

Bachelor’s degree or equivalent experience

Job description

Principal Data Engineering - Remote - CST

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.

Description -

As a Principal Data Engineering professional 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. during Central time zone business hours as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

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.

Qualifications -

Required Qualifications:

• Bachelor’s degree or equivalent experience (such as an additional 8+ years of data engineering experience)
• 10+ years of experience in data engineering, data integration, data modeling, data?f