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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Ambience Healthcare - **Location:** United States - **Experience:** Expert - **Salary:** $200,000.0 - $250,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Data Analysis, Data Validation, Information Engineering, Extract Transform Load (ETL), Data Systems, Database Queries, Python (Programming Language), Operational Data Store, Operational Databases, Performance Tuning, Raw Data, Role-Based Access Control, SQL Databases, Tableau (Software), TypeScript, Data Ingestion, Snowflake, Data Lakes, Real Time Data, Software Coding, Looker Analytics, Data Pipelines - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/senior-data-engineer-ambience-healthcare-8988840 ## About the Role * 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), and familiarity with dbt, orchestration tools (Airflow, Dagster), or BI tools (Looker, Tableau, Mode). ## Description Ambience runs on data: which clinicians are adopting the product, how much time it saves them, whether documentation quality holds up across specialties. Getting those answers right-and getting them fast, reproducibly, and in a form a customer can verify-is a hard data engineering problem, and it's the one you'll own. 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. What You'll Do: * 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)