Summary
UnitedHealth Group's Optum organization delivers technology-enabled care and health services. The Data Engineer will architect, build, and maintain enterprise ETL/ELT pipelines across on-premises and cloud environments, while developing data models, quality controls, security mechanisms, and CI/CD automation. The role also involves collaborating with Agile teams and developing responsible AI-powered solutions for complex business challenges.
Responsibilities
- Design, build, and maintain enterprise ETL/ELT data pipelines integrating data from on-premises and cloud platforms into unified data repositories using Snowflake and Apache Airflow
- Develop complex data transformation routines, SQL stored procedures, and Python scripts to clean, normalize, and aggregate high-volume datasets
- Implement data de-identification, row-level security, and data masking mechanisms in accordance with enterprise data governance standards
- Establish automated data quality validation, monitoring, and error-handling routines using tools such as Great Expectations or Soda
- Create logical and physical data models (e.g., dimensional modeling, star schemas, Data Vault) to optimize analytics performance and data integrity
- Support CI/CD pipeline automation and deployment for data engineering workflows using Git and GitHub Actions
- Optimize data pipeline performance, query execution times, and resource utilization in cloud data platforms
- Collaborate within Agile/Scrum cross-functional teams to translate business requirements into scalable technical data architectures
- Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI
Skills
- 3+ years Proven hands-on experience in a Data Engineer role building scalable ETL/ELT data pipelines
- 2+ years' Experience with Azure cloud services (Blob Storage, Azure Data Factory, Azure Functions, Key Vault) or Databricks
- 2+ Experience with version control and CI/CD deployment pipelines using Git and GitHub Actions
- 1+ Proficiency in Python for data processing, scripting, and pipeline automation
- Bachelor's degree or higher in Computer Science, Information Technology, Database Management, or a related field
- In-depth knowledge of Snowflake architecture, performance tuning, data masking, and access control policies
- Experience orchestrating Airflow data tasks to run on Kubernetes and creating Docker containers
- Strong understanding of data modeling techniques (e.g., Star Schema, Dimensional Modeling, Data Vault) and data warehousing principles
- Experience using data quality frameworks such as Great Expectations or Soda
- Familiarity with open-source languages and environments such as Scala, Java, or Linux in Agile/DevOps workflows
- Experience orchestrating data workflows using Apache Airflow
Qualifications
Must Haves
- 3+ years Proven hands-on experience in a Data Engineer role building scalable ETL/ELT data pipelines
- 2+ years' Experience with Azure cloud services (Blob Storage, Azure Data Factory, Azure Functions, Key Vault) or Databricks
- 2+ Experience with version control and CI/CD deployment pipelines using Git and GitHub Actions
- 1+ Proficiency in Python for data processing, scripting, and pipeline automation
Nice to Haves
- Bachelor's degree or higher in Computer Science, Information Technology, Database Management, or a related field
- In-depth knowledge of Snowflake architecture, performance tuning, data masking, and access control policies
- Experience orchestrating Airflow data tasks to run on Kubernetes and creating Docker containers
- Strong understanding of data modeling techniques (e.g., Star Schema, Dimensional Modeling, Data Vault) and data warehousing principles
- Experience using data quality frameworks such as Great Expectations or Soda
- Familiarity with open-source languages and environments such as Scala, Java, or Linux in Agile/DevOps workflows
- Experience orchestrating data workflows using Apache Airflow
Benefits
- Flexibility to telecommute from anywhere within the U.S.
- A comprehensive benefits package
- Incentive and recognition programs
- Equity stock purchase
- 401k contribution
- Career development opportunities