Senior Manager, IT Data Engineering

What you'll do

• Design and implement scalable, secure, and high-performance data solutions in AWS and Databricks environments.
• Develop and maintain ELT pipelines using AWS services, Apache Airflow, and Databricks.
• Translate business needs from Finance, Procurement, and IT into clear technical approaches and production-grade solutions.
• Define and enforce data engineering standards, architectural patterns, and data governance frameworks.
• Manage data models, schema designs, and integration processes across various source systems and target platforms.
• Establish data quality metrics, service-level agreements, and monitoring mechanisms to ensure data integrity.
• Implement AI-powered automation to improve data workflows and operational efficiency.
• Ensure compliance with healthcare regulatory requirements including HIPAA, SOC 2, and 21 CFR Part 11.

What we're looking for

• Bachelor’s or master’s degree in computer science, Data Engineering, Data Science, or a related field, or equivalent practical experience.
• 3–6+ years of experience in Data Engineering with a track record of designing and deploying data pipeline solutions at scale.
• At least 2+ years of experience building complex data science, AI/ML, or large-scale analytics solutions.
• Proficiency in Python and SQL, with familiarity with TypeScript/JavaScript or systems programming languages like Go or Rust.
• Experience with CI/CD platforms (e.g., GitHub Actions), Docker, infrastructure-as-code, and cloud-native architecture patterns.
• Hands-on experience building and operating data and AI platforms on AWS, including S3, Glue, Lambda, IAM, Bedrock, and Databricks Unity Catalog.
• Proficiency with Databricks (Spark), Airflow, Tableau, Genie Spaces, and related business intelligence and analytics technologies.
• Strong understanding of data privacy, security, and regulatory requirements in healthcare, including HIPAA, SOC 2, and 21 CFR Part 11.