Senior Data Engineer

Role Overview

• Build and operate production-grade ingestion pipelines from core clinical, operational, and third-party systems into our Databricks lakehouse
• Develop and maintain dbt models that turn raw data into clean, well-documented, analytics-ready datasets
• Establish data quality, testing, and monitoring practices that make pipelines reliable and trustworthy
• Help shape ingestion patterns and architecture standards alongside the Principal Data Engineer
• Enable company-wide metrics for care outcomes and operations
• Collaborate with cross-functional leads to develop and iterate on a suite of core operational dashboards, ensuring teams have the self-service tools they need to track company metrics and outcomes.
• Design, build, and operate production data pipelines across clinical, operational, and third-party systems using API-based ingestion, Change Data Capture (CDC), and event
• or webhook-driven patterns
• Build and maintain transformation layers in dbt, including tests, documentation, and reusable models
• Develop and refine core analytical and longitudinal data models used across the company
• Implement testing, monitoring, and observability to ensure data quality, pipeline reliability, and system performance
• Apply strong engineering fundamentals to improve the scalability, performance, and cost-efficiency of data systems on AWS and Databricks
• Partner with Product to support metric definitions, outcome measurement, and reporting needs
• Contribute to engineering standards, code review, and a culture of knowledge sharing and continuous improvement
• Partner with business, product, and engineering stakeholders to design and build intuitive data visualizations and dashboards that drive actionable insights and program visibility.

Requirements

• 5+ years of experience in data or backend engineering roles with significant data platform responsibility
• Hands-on experience building and operating production-grade data pipelines and ingestion frameworks
• Strong proficiency in SQL and Python for data ingestion, processing, and transformation
• Experience with a cloud data platform; experience with AWS and Databricks (or a comparable Spark-based lakehouse) strongly preferred
• Experience building SQL-based transformation workflows; hands-on experience with dbt preferred
• Strong computer science fundamentals, including comfort reasoning about distributed systems and data processing at scale
• Ability to diagnose and resolve performance, reliability, and data quality issues in complex systems
• Strong ownership mindset and comfort operating in ambiguous, fast-growing environments
• Clear communicator able to partner effectively with technical and non-technical stakeholders
• Experience building dashboards or analytical outputs used by executives and frontline teams.

Tech Stack

• AWS
• Cloud
• Distributed Systems
• Python
• Spark
• SQL

Benefits

• Equity compensation package
• Comprehensive benefits including medical, dental, and vision
• 401k
• Flexible PTO policy
• take the time you need to recharge
• $1,000 home office stipend
• We provide the equipment needed for this role.
• Opportunity for rapid career progression with plenty of room for personal growth.