Senior Software Engineer - Data Engineering

UnitedHealth Group•Brentwood, TN

5d•$91,700 - $163,700•Remote

About The Position

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 diversity and inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together. You will enjoy the flexibility to telecommute from anywhere within the U.S. as you take on some tough challenges.

Requirements

Bachelor’s degree in CS or IT or Software Engineering related field
7+ years of Data Engineering experience building enterprise-scale ETL/ELT solutions (e.g., ADF, DataStage, Talend, or equivalent)
4+ years of experience with Azure public cloud including Databricks and Snowflake
3+ years of hands-on experience with Unix/Linux shell scripting for data processing and automation
3+ years of experience with Oracle PL/SQL development for data transformation, performance tuning, and production workloads
3+ years of production support experience, including on-call rotations, incident resolution, and root cause analysis
2+ years of experience with high-level programming languages, such as Python, Java, or Node.js, with Python preferred

Nice To Haves

Excellent written and verbal communication skills, with the ability to explain data and AI concepts clearly
Prior technical or people leadership experience, including ownership of complex systems
Demonstrated experience mentoring and developing junior Engineers

Responsibilities

Design, build, and operate scalable data engineering platforms using modern ETL/ELT frameworks, including Azure Data Factory, Delta Lake, and cloud-native pipelines
Architect modular, reusable data systems that support batch and streaming workloads, advanced analytics, and AI/ML use cases
Influence overall data and AI platform architecture, including lakehouse design, metadata management, and data quality frameworks
Develop and optimize PL/SQL, Python, and Unix-based data processing solutions for high-volume, low-latency data pipelines
Enable Generative AI use cases by designing structured and unstructured data pipelines to support NLP, prompt engineering, vectorization, and inference workflows
Drive code reusability and standardized data patterns across teams through shared frameworks, libraries, and design standards
Ensure mature DevOps and DataOps practices, including CI/CD, automated testing, monitoring, incident response, and cost optimization
Deeply analyze ambiguous business and data problems, translating them into robust data engineering and AI solutions that deliver measurable business value
Lead adoption of best practices in data modeling, pipeline design, security, and governance, especially in regulated environments
Continuously assessing and modernizing existing data platforms, improving performance, reliability, scalability, and AI readiness
Partner with business, analytics, data science, and product leaders to manage delivery in an agile framework, rapidly delivering insights and AI-enabled capabilities
Mentor and coach engineers in data engineering, cloud, and Generative AI technologies, raising overall team capability
Attract and grow talent through strong technical leadership, effective interviewing, community engagement, and training junior interviewers
Communicate complex data and AI concepts clearly to both technical and non-technical stakeholders, including leadership presentations and solution demos
Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI