Job Description

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.

We are seeking a highly experienced Lead Data Engineer with over 8 years of experience in software development, architecture, and enterprise data engineering. The ideal candidate brings deep expertise in designing scalable, cloud-based data solutions, driving data strategy, and enabling high-performance data ecosystems across Azure, GCP, and Snowflake platforms.

Primary Responsibilities:

• Data Architecture & Engineering
• Architect and design end-to-end scalable data solutions leveraging Azure, GCP, and Snowflake ecosystems
• Develop and implement Snowflake and data warehousing architectures to support enterprise analytics and AI initiatives
• Design and optimize ETL/ELT pipelines using tools such as Azure Data Factory, Databricks, and Airflow (Cloud Composer)
• Lead development of reusable frameworks, utilities, and automation scripts using Python, PySpark, and Pandas
• Enable streaming and batch data integration across structured, semi-structured, and unstructured data sources
• Cloud & Platform Engineering
• Build and optimize data solutions on:
• Azure (ADLS, Data Factory, Databricks, Synapse)
• Snowflake (performance tuning, cost optimization, workload management)
• Drive cluster optimization strategies to improve performance and reduce operational costs
• Collaborate with DevOps teams to implement CI/CD pipelines and infrastructure best practices
• Data Governance & Quality
• Ensure security-by-design principles across all data platforms
• Define and enforce data standards, models, and best practices aligned with enterprise strategy
• Performance Optimization
• Optimize data processing using:
• Partitioning, bucketing, and indexing strategies
• Advanced SQL and query tuning techniques
• Cluster scaling and workload distribution
• Improve system efficiency and cost through resource optimization and intelligent scaling policies
• Big Data & Advanced Analytics
• Perform data engineering using Hadoop ecosystem technologies (Hive, Pig, PySpark)
• Enable analytics and reporting solutions through integration with tools like Power BI
• Support advanced use cases including data science, AI/ML pipelines, and real-time analytics
• 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 regards 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:

• Undergraduate degree or equivalent experience
• 8+ years of experience in software development, data engineering, and architecture
• 2+ years of focused experience in data architecture and cloud data platforms
• Experience with AI/ML, data platforms, or large-scale digital transformation initiatives
• Hands-on experience with:
• PySpark, Python, Pandas
• SQL and database design
• Proven experience in:
• Data modeling and database design
• Building scalable data pipelines and architectures
• Performance tuning and cost optimization
• Proven expertise in:
• Azure Data Services (ADF, ADLS, Databricks)
• Snowflake Architecture and Optimization
• Proven incorporate an AI builder mindset into the delivery lifecycle

Preferred Qualifications:

• Cloud Platforms: Azure, GCP, Snowflake
• Data Engineering: Azure Data Factory, Databricks, Airflow (Composer)
• Programming: Python, PySpark, Pandas
• Visualization: Power BI

Core Competencies

• Enterprise Data Architecture
• Cloud Data Engineering (Azure & GCP)
• Big Data & Distributed Processing
• Data Warehousing & Lakehouse Design
• SQL & Data Modeling
• Data Governance & Security
• Performance Optimization
• Leadership & Stakeholder Management

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.