Senior Data Engineer

Ambience is building the AI intelligence platform that restores humanity to healthcare and drives meaningful ROI for health systems. Our technology helps providers focus on delivering great care by removing administrative burdens. Ambience delivers real-time coding-aware documentation and clinical workflow support across ambulatory, emergency, and inpatient settings at top health systems in North America. Recognized as #1 for Improving the Clinician Experience by KLAS Research, named one of the Next Big Things in Tech by Fast Company, and selected as a LinkedIn Top Startup in 2024 and 2025, we’re backed by Oak HC/FT, Andreessen Horowitz (a16z), OpenAI Startup Fund, and Kleiner Perkins.

About the role

Ambience runs on data: which clinicians are adopting the product, how much time it saves them, and whether documentation quality holds up across specialties. As a Senior Data Engineer, you'll build and run the pipelines that ingest clinical and operational data, model it into governed metrics, and put trusted self-service analytics in front of every team at the company. You'll work cross-functionally with product managers, engineers, clinicians, and GTM to turn raw data into the numbers the whole company—and our customers—make decisions on. If a metric is wrong, stale, or can't be explained, that's yours to fix—and the credibility of our platform rides on you getting it right.

Our Engineering roles are hybrid in our SF office 3x/week.

Responsibilities

• Own the Trust Layer: Build and run the pipelines that ingest, validate, and transform clinical and operational data at scale—so the metrics powering our AI story are accurate, reproducible, and defensible. If the data breaks, you own the fix.
• Enable Insights Across Teams: Partner with engineering, clinical, and product teams to design clear, actionable dashboards and analytics that guide decision-making and improve healthcare outcomes.
• Support Scalable Infrastructure: Apply best practices around warehousing, orchestration (Dagster), governance, and RBAC to keep our data systems secure, performant, and ready for rapid innovation as load increases.
• Automate Data Ingestion Workflows: Build file-based ingestion pipelines enabling plug-and-play onboarding of external data sources. Develop automated validation, triggering, and error-handling mechanisms for real-time data availability.
• Establish Validation & Transformation Pipelines: Implement data validation frameworks using Python or TypeScript, and design transformation layers (SQL, dbt) that standardize and cleanse raw data for analysis and operational workflows.
• Deliver Governed, Trusted Analytics: Build and maintain governed metrics and analytical schemas in SQL that stand up to customer and third-party verification, and enable tiered self-service so every employee—technical or not—can answer their own questions without waiting on the data team.

Requirements

• 5+ years in a production Data Engineering role, with hands-on Snowflake experience (data modeling, performance tuning, warehouse administration).
• Strong SQL skills and proficiency in Python; experience building ETL/ELT pipelines, data lakes, or warehouses in modern cloud environments.
• Solid grasp of data validation, schema design, and scalable architecture.
• A clear communicator who can bridge technical and non-technical teams, gather requirements, and present to cross-functional stakeholders.
• Mission-driven, thrives in a fast-paced startup environment, and takes ownership of deliverables.

You'll thrive here if you've owned a production pipeline end-to-end and know why observability matters because you've been paged when data went stale; you move fast and take real ownership of data quality; and you're comfortable making calls without a fully-specified ticket. This probably isn't the role for you if you need detailed specs before writing code, or want to stay heads-down away from clinical and business stakeholders.

Nice-to-haves

• Early-stage startup experience.
• Background in regulated industries (healthcare, finance).
• Familiarity with dbt, orchestration tools (Airflow, Dagster), or BI tools (Looker, Tableau, Mode).

Pay

The base compensation for this role is approximately $200,000–$250,000 per year, excluding equity or bonus targets. We’ve intentionally allocated a wider range so that candidates have more flexibility to choose the desired cash/equity split that works for them. Philosophically, we lean towards generous equity grants so that our team truly gets to share in the impact they create. We encourage you to still apply if you're outside of the range: we take an individualized approach to ensure that compensation accounts for all of the life factors that matter for each candidate.

Benefits

• Comprehensive medical, dental, and vision coverage for you and your dependents.
• 401(k) with a company match of up to 3% of base salary.
• A remote-friendly culture (with a San Francisco HQ) and full equipment provisioning to ensure you can work effectively from wherever you’re based.
• Parental leave to support your family needs.
• Annual company-wide off-sites, team off-sites, and regular team lunches and all-hands gatherings, with travel, lodging, and meals covered.
• Flexible time off with no annual cap, company-wide holidays, and an annual holiday shutdown from December 24–January 1 designed to support real rest and long-term sustainability.

Life at Ambience

• Work on mission-critical AI technology that directly improves clinicians’ day-to-day lives and health system financial health across some of the most complex, high-stakes workflows in the world.
• Join a “dream team” culture where we hire exceptional people, expect exceptional outcomes, and invest deeply in feedback and continuous growth. We operate as a championship team, and that means being ok with hard, uncomfortable, ambiguous problems that lead to real greatness.
• Operate with real ownership and accountability in an environment where there are no bystanders: If something is broken, we fix it! You will have meaningful autonomy and be expected to drive work to completion.