Staff Data Engineer

The Data Engineering Platform team is responsible for building the foundational data systems that power Collective Health’s operations and insights. Our team enables reliable, governed, and scalable data flows that support analytics, data science, and external reporting across the company. The Data Ingestion & Modeling team focuses specifically on transforming raw data into robust, trusted data warehouse models that serve as the single source of truth for downstream use.

As a Staff Data Engineer, you’ll lead the technical strategy and execution for the ingestion and modeling layer of our data platform. You will work hands-on to design, build, and optimize data pipelines and dimensional models, while also setting technical direction and mentoring a small team of 2–4 data engineers. This is a key technical leadership role—not a people management role—that will shape how we transform raw data into clean, analytics-ready datasets. You’ll report to the Director of Data Engineering Platforms and work closely with peers across analytics, product, and operations to deliver data solutions that matter.

• Lead technical design and implementation of ingestion and transformation pipelines from various source systems into our centralized data warehouse.
• Develop, maintain, and evolve dimensional models (facts and dimensions) to support analytics, reporting, and data science.
• Partner with data analysts, product managers, and domain experts to ensure models are aligned with business needs and definitions.
• Review code, mentor teammates, and raise the bar on engineering quality and operational reliability.
• Own and improve the team’s ELT workflows, including orchestration, testing, observability, and CI/CD practices.
• Drive consistency and reuse across domains through shared data modeling patterns, frameworks, and tools.
• Help prioritize technical debt and contribute to long-term architecture decisions in collaboration with other data platform leads.

• 12+ years of experience as a data engineer or analytics engineer, with deep experience designing and building data warehouse models.
• Expertise in modern ELT pipelines, data modeling (especially dimensional models), and warehouse technologies like Snowflake, Databricks, or BigQuery.
• Strong proficiency in SQL and at least one programming language (e.g., Python or Scala).
• Experience working with orchestration tools such as Airflow or DBT to manage pipeline workflows.
• A strong sense of data governance, data quality, and testing best practices.
• A collaborative mindset with the ability to influence and guide peers through technical leadership, not management.
• Experience in healthcare or other regulated data environments is a plus, but not required.

This is a hybrid position based out of one of our offices: San Francisco, CA, Plano, TX, or Lehi, UT. Hybrid employees are expected to be in the office two days per week.#LI-hybrid 

The actual pay rate offered within the range will depend on factors including geographic location, qualifications, experience, and internal equity. In addition to the salary, you will be eligible for stock options and benefits like health insurance, 401k, and paid time off. Learn more about our benefits at https://jobs.collectivehealth.com/benefits/.