Senior Full Stack Data Engineer

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The Senior Full Stack Data Engineer will collaborate with various stakeholders to develop scalable data engineering solutions, design data pipelines, and ensure data quality and operational efficiencies.

Responsibilities:

• Collaborate closely with product owners, business users, and stakeholders to translate data product and reporting requirements into scalable, reliable data engineering solutions, incorporating feedback iteratively throughout the delivery lifecycle
• Design, develop, and maintain end to end data pipelines across staging, integration, and consumption layers, leveraging Azure Data Factory, DBT, Snowflake SQL, and metadata driven frameworks
• Develop and optimize high performance SQL queries, views, and stored procedures to support analytics, reporting, and provide guidance to analytics team members on effective and cost-efficient usage
• Architect, Develop and support data integration processes including batch file ingestion and automated extracts
• Partner with internal stakeholders to understand business objectives, study requirements, and identify appropriate technical solutions, integration patterns, and data models that balance performance, scalability, and maintainability
• Serve as a technical subject matter expert and mentor, providing training, design guidance, and code reviews for associates on data engineering best practices, Snowflake optimization, and ADF/DBT pipeline design
• Author and maintain detailed technical documentation, including data mappings, record layouts, file specifications, interface contracts, workflow diagrams, and operational runbooks for data loads and extracts
• Continuously evaluate and improve data quality, monitoring, and operational efficiencies
• Collaborate with business and technical partners to support data acquisition initiatives, including onboarding new data sources, developing business justifications, and executing secure, compliant data transfers
• Communicate complex technical concepts clearly through written documentation, presentations, and discussions with audiences ranging from technical teams to senior leadership
• Foster a collaborative, inclusive environment that promotes knowledge sharing, continuous improvement, and professional development across the team
• Demonstrated ability to work independently, manage multiple priorities, and adapt to evolving business and technology requirements
• Demonstrated analytical and troubleshooting skills, with the ability to diagnose pipeline failures, data anomalies, and performance bottlenecks

Requirements:

• High School Diploma/GED OR equivalent experience
• 8+ years of hands-on data engineering experience, with an emphasis on enterprise data warehousing and ETL architecture
• 6+ years of ETL development experience designing and building pipelines, dataflows using Azure Data Factory and/or Snowflake, including parameterized and metadata driven designs
• 6+ years of experience using Snowflake database including creating data ingestion and extraction through stored procedures and leveraging Snowflake native utilities
• 6+ years of experience with GitHub version control systems including code merges and cross environment deployments using CD/CI pipelines
• 6+ years of Python experience, particularly for data processing, orchestration, or validation workflows
• 6+ years of experience designing or consuming APIs and service based integrations (REST) within Snowflake or ADF based workflows
• 5+ years of scripting experience (Batch, PowerShell, or similar) to support automation and operational tasks specifically on Azure platform
• Experience processing both structured and semi structured data (e.g., fixed width files, delimited files, JSON, XML)
• Hands‑on expertise in Power BI, including: DAX, Semantic model design, Performance tuning
• Hands‑on expertise in React
• .Net development experience