Bachelor's degree in Computer Science, Engineering, or a related technical field
12+ years of professional experience in data engineering, data products development, AI tools, including technical leadership
Hands-on experience with AI Tools or platforms, building and deploying AI models for analytics leveraging LLM, RAG and Gen AI
Qualification wording
Bachelor's degree in Computer Science, Engineering, or a related technical field
12+ years of professional experience in data engineering, data products development, AI tools, including technical leadership
Hands-on experience with AI Tools or platforms, building and deploying AI models for analytics leveraging LLM, RAG and Gen AI
Education & alternatives
Required Qualifications:
- Bachelor's degree in Computer Science, Engineering, or a related technical field
- 12+ years of professional experience in data engineering, data products development, AI tools, including technical leadership
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
Python
Scala
SQL
Azure
Databricks
Kafka
NoSQL
Snowflake
Spark
Where the posting names them
- Design and implement cloud-native data platforms (e.g., Azure Data Lake, Databricks, Snowflake) with batch, streaming
- Build robust pipelines using Python/Scala, Spark, SQL, Kafka, and orchestration (Azure Data Factory)
- Design and deploy REST/GraphQL APIs for curated data products, ML inference, and feature services
- Hands-on experience with AI Tools or platforms, building and deploying AI models for analytics leveraging LLM, RAG and Gen AI
- Data Engineering Expertise: Hands-on experience with Azure, Apache Spark, Databricks (using Scala and Python), and Azure Data Factory
- Database Management: Solid experience with SQL and NoSQL databases for efficient data storage and querying
- Data Engineering Expertise: Hands-on experience with Azure, Apache Spark, Databricks (using Scala and Python), and Azure Data Factory
- Database Management: Solid experience with SQL and NoSQL databases for efficient data storage and querying
- Version Control: Proficiency with Git or similar systems
Primary Responsibilities:
- Design and implement cloud-native data platforms (e.g., Azure Data Lake, Databricks, Snowflake) with batch, streaming
- Build robust pipelines using Python/Scala, Spark, SQL, Kafka, and orchestration (Azure Data Factory)
- Optimize cost, performance, and reliability; implement observability (lineage, logging, metrics, alerting)
- Advanced understanding of data architecture and cloud solutions, especially in Azure
- Mentor a team of engineers; define coding standards, reviews, and engineering OKRs
Complete your application on careers.unitedhealthgroup.com. The employer’s form will show what is required.
Applying through Radancy (TalentBrew)
Radancy (TalentBrew) runs the employer’s careers site, but the application itself usually runs on another system, often Workday or Taleo. The advice for that system applies once you click Apply.
Yes. We’ve followed one other Principal Data Engineering job there since June 2026. It came down after 0 days.
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About UnitedHealth Group
People
About 390,000 in 2025, down 2% from the year before.Annual report (SEC Form 10-K)
Company
Listed as UNH.
H-1B visas
11 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
Demand for Data Engineer roles
New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
August 17Last week
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
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.
Primary Responsibilities:
Design and implement cloud-native data platforms (e.g., Azure Data Lake, Databricks, Snowflake) with batch, streaming
Build robust pipelines using Python/Scala, Spark, SQL, Kafka, and orchestration (Azure Data Factory)
Design and deploy REST/GraphQL APIs for curated data products, ML inference, and feature services
Advanced understanding of data architecture and cloud solutions, especially in Azure
Mentor a team of engineers; define coding standards, reviews, and engineering OKRs
Translate business needs into scalable data solutions or products, manage stakeholder expectations and delivery timelines
Comply with all applicable Company policies, procedures, and business directives, changes including those relating to work location, team assignments, work schedules, and flexible work arrangements
Required Qualifications:
Bachelor's degree in Computer Science, Engineering, or a related technical field
12+ years of professional experience in data engineering, data products development, AI tools, including technical leadership
Hands-on Data Engineering Lead to architect, build, and scale modern data platforms that power analytics, AI, and real-time APIs
Hands-on experience with AI Tools or platforms, building and deploying AI models for analytics leveraging LLM, RAG and Gen AI
Data Engineering Expertise: Hands-on experience with Azure, Apache Spark, Databricks (using Scala and Python), and Azure Data Factory
Database Management: Solid experience with SQL and NoSQL databases for efficient data storage and querying
Version Control: Proficiency with Git or similar systems
Agile & Testing: Familiarity with Agile methodologies, unit testing, and test automation frameworks
AI: GitHub Copilot, M365 Copilot, LLM Models, Gen AI
Solution Architecture: Ability to design, implement, and integrate solutions with robust data security measures
Performance Optimization: Ensure cross-browser compatibility and optimize applications for scalability and high performance
Server-Side Development: Design, develop, and maintain API services and server-side applications
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.