The Principal Data Engineer is a senior individual contributor responsible for designing, building, and scaling enterprise data platforms and data pipelines. This role combines cloud-based data architecture ownership with hands-on technical execution across cloud and hybrid environments to support large-scale data, analytics, and machine learning initiatives. Working within Optum Technology, you will partner across engineering, BI, and product teams to ensure high data reliability, performance, and security. You will also leverage enterprise-approved AI tools and modern data platforms (Databricks, Snowflake, GCP/Azure/AWS) to automate workflows, optimize pipelines, and drive continuous platform innovation.
You'll enjoy the flexibility to work remotely * from anywhere within the U.S. 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:- Lead the design and implementation of cloud-based and hybrid data architectures, platforms, and enterprise data solutions
- Build, optimize, and maintain scalable ELT/ETL data pipelines utilizing Python, SQL, Spark/PySpark, and modern data platforms (e.g., Databricks, Snowflake)
- Design, develop, and deploy AI-powered solutions and automated data engineering workflows to address complex business challenges with an emphasis on responsible AI practices
- Design and operationalize ML pipelines in partnership with Data Science, covering feature engineering, training and inference data flows, model versioning, and automated retraining or scoring workflows
- Leverage enterprise-approved AI tools to streamline technical workflows, automate data tasks, and drive continuous platform improvement
- Evaluate emerging data engineering trends, cloud technologies, and AI capabilities to inform solution design and strategic innovation
- Partner with Analytics/BI, Data Science, and Product teams to deliver trustworthy, high-performing datasets and metric frameworks
- Ensure data quality, observability, lineage, and documentation across data pipelines using tools like dbt, Great Expectations, and cloud logging/monitoring
- Implement security, IAM, encryption, PII handling, and regulatory compliance controls across all data storage and pipeline layers
- Provide hands-on technical leadership, solution design reviews, and mentorship to junior and senior engineers
- Troubleshoot and resolve complex data pipeline incidents, driving root cause analysis and preventive platform enhancements
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:- 7+ years of experience in data engineering, enterprise data platform development, or data architecture roles
- 5+ years of hands-on experience building and optimizing scalable ELT/ETL data pipelines using Python, SQL, and Spark/PySpark
- 3+ years of experience developing data models and processing workflows on modern data platforms such as Databricks or Snowflake
- 3+ years of hands-on experience with major cloud platforms (GCP, Azure, or AWS) including cloud storage, IAM security controls, and hybrid architectures
- 3+ years of experience building CI/CD workflows for data pipelines and managing Infrastructure-as-Code (IaC) using Terraform
- 3+ years of experience implementing batch and streaming/micro-batch processing solutions for near-real-time data use cases
- 3+ years of experience building and operationalizing ML data pipelines, including feature engineering, training/inference data flows, and automated model retraining or scoring workflows (e.g., MLflow, Databricks ML, Vertex AI, Azure ML, or SageMaker)
Preferred Qualifications:- Bachelor's degree in Computer Science, Data Engineering, Information Technology, or a related technical field (or equivalent experience)
- Relevant cloud or data certifications (e.g., Databricks Certified Data Engineer, Snowflake Certified, or GCP Professional Data Engineer)
- Experience with data quality, observability, and data catalog tools (e.g., Great Expectations, dbt tests, Cloud Monitoring, Data Catalog)
- Experience working in healthcare, contact-center analytics, or highly regulated enterprise environments
Location- Solid preference for Minnesota based candidates
- Flexibility for U.S. based candidates if local talent is not available
*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 salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $112,700 - $193,200 annually based on full-time employment. We comply with all minimum wage laws as applicable.
Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.
