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Data Engineer

About Us:

Ambience is developing the most capable AI systems for healthcare and medicine. As healthcare costs soar to 17.3% of US GDP and a projected shortage of 100,000 physicians within the next decade, the need for AI is critical. Our frontline healthcare workers are overwhelmed, with only 27% of the average clinician's day spent on direct patient care.

Our vision is to equip every healthcare worker with an advanced AI co-pilot. We believe that people, augmented by AI, will enable us to deliver higher quality healthcare at a lower cost, improving the experience for everyone involved.

Headquartered in San Francisco, we have secured $100M in funding from top investors, including Kleiner Perkins, OpenAI Startup Fund, Andreessen Horowitz, Optum Ventures, Human Capital, and Martin Ventures. We collaborate with leading AI experts such as Jeff Dean, Richard Socher, Pieter Abbeel, and AIX Ventures.

Join us in the endeavor of accelerating the path to safe & useful clinical super intelligence by becoming part of our community of problem solvers, technologists, clinicians, and innovators.

The Role:

As a Data Engineer at Ambience, you’ll play a pivotal role in building the Data Platform from the ground up to power cutting-edge healthcare AI. Your work will ensure seamless data ingestion, high data quality, and actionable insights across the company. This is a high-impact, cross-functional role that partners closely with product managers, engineers, and business stakeholders to architect robust pipelines and deliver analytics solutions that power data-informed decisions. From automating data ingestion to delivering insights to clinicians and product teams, you’ll architect systems that fuel everything we do with data.

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

What You’ll Do:

  • Power AI with Great Data: Build scalable pipelines to ingest, validate, and transform data—laying the foundation for reliable AI systems and model development.

  • 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.

  • Architect Scalable Infrastructure: Define best practices around warehousing, indexing, and governance to ensure our data systems are secure, maintainable, and ready for rapid innovation.

  • 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 Actionable Analytics: Maintain analytical schemas and materialized views in SQL. Build dashboards that make data accessible and insightful for technical and non-technical users alike.

Who You Are:

Technical Expertise

  • 3+ years in a production Data Engineering role and 2+ years in Software Engineering (or equivalent).

  • Strong command of SQL for performance tuning, transformations, and data modeling.

  • Proficient in scripting languages like Python or TypeScript.

  • Comfortable building and maintaining data pipelines (ETL/ELT), data lakes, or warehouses in modern cloud environments.

  • Strong understanding of data validation, schema design, and scalable architectures.

Collaborative Communicator

  • Bridges technical and non-technical teams with ease.

  • Leads discussions, gathers requirements, and simplifies complex data concepts for diverse stakeholders.

  • Comfortable drafting design docs and presenting to cross-functional teams.

Mission-Aligned

  • Passionate about mission-driven work and excited by the opportunity to impact healthcare outcomes with data.

  • Thrives in a fast-paced, early-stage environment; takes extreme ownership of deliverables.

Nice-to-Haves

  • Experience in early-stage startups or building systems from scratch.

  • Prior work in highly regulated industries (e.g., healthcare, finance).

  • Involvement in hiring or mentoring for Data Engineering roles.

Pay Transparency

The base compensation for this role is approximately $160,000–$247,000 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.

Are you outside of the range? We encourage you to still apply: we take an individualized approach to ensure that compensation accounts for all of the life factors that matter for each candidate.

Being at Ambience: 

  • An opportunity to work with cutting edge AI technology, on a product that dramatically improves the quality of life for healthcare providers and the quality of care they can provide to their patients

  • Dedicated budget for personal development, including access to world class mentors, advisors, and an in-house executive coach

  • Work alongside a world-class, diverse team that is deeply mission aligned

  • Ownership over your success and the ability to significantly impact the growth of our company

  • Competitive salary and equity compensation with benefits including health, dental, and vision coverage, paid maternity/paternity leave, quarterly retreats, unlimited PTO, and a 401(k) plan

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CEO of Ambience Healthcare
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Average salary estimate

$203500 / YEARLY (est.)
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$160000K
$247000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Data Engineer, Ambience Healthcare

At Ambience, we are on a mission to revolutionize healthcare by leveraging advanced AI systems, and we’re looking for a Data Engineer to join our growing team in San Francisco. As a Data Engineer, you'll play a crucial role in constructing our Data Platform from the ground up, ensuring that we can seamlessly power our innovative healthcare solutions with top-notch data. Your talent for building scalable data pipelines will help us ingest, validate, and transform data, enabling our engineers and clinicians to derive actionable insights. Collaborating with product managers and other stakeholders, you’ll architect robust data systems and deliver analytical tools that empower decision-making across the organization. You’ll not only automate the ingestion of crucial data but also design validation processes that maintain our high-quality standards. If you’re passionate about translating complex data into meaningful insights and enjoy working with cross-functional teams in a fast-paced environment, this is the perfect opportunity for you to impact the future of healthcare directly. Join us at Ambience to create technologies that enhance the efficiency of healthcare providers and elevate patient care. Together, we can build the AI co-pilot that will support healthcare workers everywhere.

Frequently Asked Questions (FAQs) for Data Engineer Role at Ambience Healthcare
What are the main responsibilities of a Data Engineer at Ambience?

As a Data Engineer at Ambience, your primary responsibilities include constructing scalable data pipelines for seamless data ingestion, ensuring high data quality, and developing analytical tools that enable actionable insights for our teams. You'll collaborate closely with product managers, engineers, and business stakeholders to architect data systems that support decision-making in healthcare.

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What qualifications do I need to become a Data Engineer at Ambience?

To qualify for the Data Engineer position at Ambience, you should have at least 3 years of experience in a production Data Engineering role and 2 years in Software Engineering or equivalent. Proficiency in SQL, Python or TypeScript, and experience in building data pipelines in cloud environments are essential skills for this role.

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What technical skills are required for the Data Engineer role at Ambience?

The Data Engineer role at Ambience requires a strong command of SQL for performance tuning and data modeling, proficiency in scripting languages like Python or TypeScript, and experience with ETL/ELT processes. Familiarity with data validation frameworks and scalable architectures is also crucial to succeed in this role.

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What is the working environment like for a Data Engineer at Ambience?

At Ambience, Data Engineers work in a hybrid model, collaborating with a diverse team in our San Francisco office three days a week. The work environment is fast-paced and intellectually engaging, where innovation and creativity are highly valued as we strive to enhance healthcare through technology.

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What benefits does Ambience offer to Data Engineers?

Ambience offers a competitive salary range, equity compensation, and a comprehensive benefits package including health, dental, and vision coverage, unlimited PTO, a 401(k) plan, and dedicated budgets for personal development, which includes access to world-class mentors and an in-house executive coach.

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Common Interview Questions for Data Engineer
Can you explain the process you follow for building a data pipeline?

When asked about building a data pipeline, it's helpful to outline each stage you typically follow: data ingestion, validation, transformation, and loading. Mention the tools and technologies you utilize, such as ETL frameworks or scripting languages. Highlight your focus on maintaining data quality and performance optimization throughout the process.

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How do you ensure data quality and integrity in your engineering work?

You can explain that ensuring data quality involves implementing validation frameworks and automated checks at different stages of the data pipeline. Discuss your experience with anomaly detection, data cleansing techniques, and maintaining audit logs to track data changes, which can help prevent issues and enhance trust in the data provided.

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Describe a challenging data engineering problem you have solved in the past.

Share a specific example that details the problem, your approach to solving it, and the outcome. Highlight the analytical skills and technical knowledge you applied, while emphasizing collaboration with other teams to develop a solution that positively impacted the organization’s objectives.

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What is your experience with cloud data services?

Discuss your familiarity with cloud providers like AWS, GCP, or Azure, emphasizing the services you've used such as data lakes, warehouses, or managed databases. Highlight your ability to leverage these services to build scalable data solutions and your experience with security and compliance within cloud environments.

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How do you prioritize tasks in a project-focused environment?

Explain your approach to task prioritization by discussing your methods for assessing project requirements and timelines. Mention using agile methodologies or tools that help track progress and communicate with stakeholders to ensure alignment and efficient task management.

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Can you discuss your experience with SQL and data modeling?

Detail your proficiency with SQL, focusing on how you’ve utilized it for data modeling and performance tuning in past roles. Provide examples of complex queries you’ve written, and describe how your data models supported analytics initiatives or business intelligence needs.

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What strategies do you use to work effectively with non-technical teams?

Emphasize your communication skills and how you simplify complex data concepts for diverse audiences. Share examples of how you’ve bridged the gap between technical and non-technical teams to gather requirements and ensure successful project outcomes.

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How do you stay updated with advances in data engineering?

Discuss your commitment to continuous learning, such as attending industry conferences, participating in online courses, and following influential blogs or communities about data engineering practices and technologies. This demonstrates your proactive approach to your professional development.

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Have you ever been involved in mentoring or training junior data engineers?

Share your experiences with mentoring, including how you guided junior engineers through complex projects, provided constructive feedback, and facilitated their professional growth within the team, emphasizing how this benefitted the organization as a whole.

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Why are you passionate about working in healthcare data engineering?

Express your motivation for contributing to the healthcare industry, focusing on the positive impact technology has on patient care and healthcare providers. Highlight your desire to work at a data-driven organization like Ambience where your efforts can lead to meaningful changes in healthcare outcomes.

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Ambience Healthcare’s mission is to supercharge healthcare providers with AI superpowers.

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EMPLOYMENT TYPE
Full-time, hybrid
DATE POSTED
March 28, 2025

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