Location: Remote
You'll enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges.
Position SummaryAs a Principal Data Engineer on our Optum Technology team, you will drive data architecture, platform engineering, and AI/ML data pipeline integration to build scalable, resilient, and performant enterprise data systems. In this role, you will lead the technical design, development, and deployment of complex big data infrastructure and AI-powered data solutions. You will collaborate with software engineers, data scientists, product managers, and business leaders to build robust data pipelines, deploy machine learning applications into production, and convert healthcare data into actionable insights while emphasizing responsible AI practices
Primary Responsibilities- Design, develop, and deploy AI-powered data solutions, machine learning pipelines, and automations to address complex business challenges with an emphasis on responsible AI practices
- Architect, design, and implement complex, scalable data models, transformation frameworks, and multi-platform solutions across full technology stacks and enterprise domains
- Leverage broad expertise across big data, streaming, cloud, and relational database technologies to optimize system performance, eliminate unnecessary complexity, and build scalable scheduling and ETL/ELT pipelines
- Evaluate emerging technology trends, AI/ML frameworks, and platform automation to inform solution design, platform strategy, and enterprise innovation
- Champion adherence to enterprise security, compliance, and data governance standards, proactively identifying, mitigating, and addressing security gaps in solution design and operational workflows
- Drive a culture of continuous quality by leading root-cause analyses and building diagnostic instrumentation to demonstrate the business value of automated CI/CD chains
- Serve as a Subject Matter Expert (SME), mentor, and escalation point for complex technical challenges, fostering technical excellence across engineering teams
- Translate complex technical concepts into clear business terms, partnering with executive leadership, cross-functional stakeholders, and customers to guide strategic decisions and digital channel solutions
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- HS Diploma required
- 8 years of data engineering experience designing, building, and deploying enterprise-scale data architecture and pipelines
- 5 years of experience with relational databases, NoSQL, and cloud data warehousing platforms (e.g., Snowflake, Databricks)
- 5 years of experience in data modeling (dimensional, relational, or data vault) and schema design
- 5 years of experience with programming languages such as Python, Scala, Java, or SQL
- 3 years of experience with big data processing frameworks (e.g., Spark, Hadoop) or real-time streaming technologies (e.g., Kafka, Flink)
- 3 years of experience with cloud platforms (AWS, Azure, or GCP), infrastructure as code, and automated CI/CD pipelines
Preferred Qualifications- Experience with MLOps frameworks, model monitoring tools, or feature store platforms (e.g., MLflow, Feast, Kubeflow)
- Experience in the healthcare industry working with health data standards (e.g., FHIR, HL7, EDI) and healthcare security/compliance regulations
- Deep expertise with cloud-native data services, enterprise data governance, and metadata management tools
- Proven track record of architecting distributed systems handling large-scale unstructured and structured data sets
- Experience implementing automated testing, data quality frameworks, and responsible AI validation within deployment pipelines
- Demonstrated experience leading technical architecture design, governing data security standards, and mentoring software/data engineering teams
- 3 years of experience building, integrating, and deploying machine learning pipelines, AI models, or AI-powered data applications into production environments
*All Telecommuters 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 to $193,200 annually based on full-time employment. We comply with all minimum wage laws as applicable.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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.
