Principal Data Engineering - Remote

Optum is a global leader in health care innovation, developing cutting-edge solutions to improve health systems. As a Principal Data Engineering, you will lead data engineering teams and drive the design and implementation of machine learning infrastructure and platforms to support enterprise analytics and AI workloads.

Responsibilities:

• Lead and grow data engineering teams by mentoring engineers and fostering a solid engineering culture focused on reliability, innovation, and collaboration
• Define data platform architecture and strategy supporting enterprise analytics, AI, and machine learning workloads
• Design and maintain scalable batch and streaming data pipelines for ingestion, transformation, orchestration, and data delivery
• Develop modern data engineering platforms using technologies such as Apache Spark, Databricks, and Snowflake
• Enable AI and machine learning workflows by building feature stores, ML data pipelines, and curated data layers
• Implement data quality, governance, and observability frameworks including lineage, validation, and metadata management
• Ensure operational excellence including SLAs, SLOs, reliability, scalability, performance optimization, and cost efficiency
• Collaborate with product, analytics, platform, and security teams to translate business needs into scalable data solutions

Requirements:

• 8+ years of experience in data engineering or data platform engineering including large-scale ETL/ELT pipelines and distributed data processing systems
• 8+ years of experience programming in Python or Scala for data engineering along with advanced SQL for data transformation and analytics
• 6+ years of experience working with modern data engineering technologies; such as Apache Spark, Databricks, Snowflake, or equivalent platforms
• 5+ years of experience building and operating cloud-based data platforms on AWS, Azure, or GCP
• 5+ years of experience designing data models and storage architecture; including dimensional modeling, data lakes, or data warehouses
• 4+ years of experience leading data engineering teams or technical initiatives; including mentoring engineers and influencing architecture decisions
• 1+ years of experience with rapid prototyping and production deployment using vibe coding tools like Claude Code, Cursor, Replit, and GitHub Copilot
• Master's degree in Computer Science, Engineering, Data Science, or a related technical field
• Experience building real-time or streaming data pipelines using Kafka, Kinesis, Event Hubs, or similar technologies
• Experience with workflow orchestration tools such as Airflow, Databricks Workflows, or Prefect
• Experience implementing data governance frameworks including metadata management, lineage tracking, and cataloging tools
• Experience implementing DevOps practices for data platforms including CI/CD pipelines and Infrastructure as Code
• Experience in Healthcare or Life Sciences