Senior Data Engineer

You'll be joining at a pivotal moment: we have working infrastructure, and we're refining it from "functional" to "exemplary." This means hardening our ingestion pipelines, building and maintaining a solid data warehouse, establishing data contracts, and implementing documentation practices where data models evolve thoughtfully. You'll be a key contributor shaping how we build and scale data engineering within our Core Data team.

What you'll do

• Own and evolve our data pipeline infrastructure - designing and maintaining reliable, scalable ingestion and transformation pipelines across our practice management systems landscape and internal sources
• Own our data warehouse: drive thoughtful data modeling, ensure high data quality, and make it a trusted foundation for the Analytics and product teams who depend on it
• Define and enforce data contracts with producing teams, ensuring schema stability, clear ownership, and reliable data delivery
• Drive data model evolution: managing schema versioning, breaking change processes, and communicating impact clearly to consuming teams
• Build and maintain Reverse ETL pipelines to sync curated data back into operational systems and tools used across the business
• Establish monitoring, alerting, and incident response practices for our data systems, ensuring high availability and fast time-to-recovery
• Drive documentation culture around data - catalog, lineage, and metadata as first-class concerns, supporting governance and compliance in a regulated healthcare environment

What you'll need

• Strong software engineering experience in Python with production-grade data pipeline experience
• Hands-on experience building and maintaining data warehouses and implementing data contracts between teams
• Experience with data transformation and modeling, working with both structured and semi-structured data sources
• Practical experience with Reverse ETL
• Experience with data model evolution: versioning strategies, migration processes, and maintaining backward compatibility across consumers
• Strong experience with AWS
• Experience with Kafka or similar event streaming platforms
• Deep passion for documentation and knowledge sharing - you've championed documentation-first practices and believe undocumented data is nearly useless

Nice to have

• Familiarity with Dagster or similar workflow orchestration tools
• Exposure to data catalog tooling
• Experience working in regulated environments with security and compliance requirements