Data Engineering Consultant

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, develop, and optimize scalable data pipelines using Databricks, Apache Spark, and Python on Azure Cloud
• Implement cloud-based data solutions leveraging Azure Data Lake, and Azure Data Factory
• Collaborate with data scientists and AI teams to operationalize machine learning models and integrate them into data workflows
• Build and maintain feature stores, model input pipelines, and real-time data processing frameworks
• Ensure data quality, governance, and security across all stages of the data lifecycle
• Develop reusable frameworks and automation scripts to accelerate data engineering and AI deployment
• Participate in Agile development processes, including sprint planning, code reviews, and CI/CD using GitHub or Azure DevOps
• Work in On call shift model for production operations and support
• Design, develop, and deploy AI/ML models for business-driven use cases
• Build and maintain data pipelines for model training, inference, and monitoring
• Collaborate with data engineers to integrate AI solutions with Databricks Lakehouse architecture
• Develop and optimize ML workflows using Databricks notebooks, jobs, and workflows
• Deploy AI/ML models using APIs or batch/streaming pipelines
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regard to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

• Bachelor or Master Degree
• 6+ years of experience in Data Engineering (Python, PySpark)
• 5+ years of experience in building data pipeline, ETL using Databricks
• 3+ year experience batch operations in Databricks environment.
• Experience building queries in SQL and PL/SQL
• Good experience in working with Azure cloud deployment
• Experience working in an Agile development environment
• Experience building unit tests, executions
• Experience using a source control repository, preferably GIT
• Experience in using GenAI tools (Github Co-pilot etc.)
• Good understanding of secure coding best practices, remediation of security vulnerability general knowledge
• Proficiency in SQL, with practical experience in PostgreSQL or similar relational databases
• Proven problem solving skills, able to analyze logs and trouble shoot issues
• Proven willingness to learn new technologies and eagerness to think outside the box

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.

#Nic