We’re Heidi.

We're building the future of healthcare by giving every clinician the earth's finest AI Care Partner. Our platform has absorbed the administrative chaos of 175 million patient visits and supported 67 million clinical hours. Today, we support 2.8 million patient sessions a week across 190+ countries, in 110 languages and over 200 specialties.

Healthcare systems are failing us; clinicians spend more time on documentation than on patients, and the human connection that makes medicine worth practicing is eroding. Our mission is simple: double the world’s capacity for care and strengthen the human connection at its heart.

We found product-market fit with a freemium medical scribe that clinicians love. Now, we're expanding. Every task a clinician hands to Heidi is a patient who feels more attended to, a health system unclogged, and a clinician who gets to be a clinician again.

We’ve grown annual recurring revenue from $1 million to $50 million in two years.

To go further, we’ve secured US$340 million: a $100 million Series C led by Blackbird, with Phoenix Court, Point72 Private Investments and Headline, alongside a $240 million growth investment led by General Catalyst’s Customer Value Fund.

If you want to join us in doing work worth shipping, jump in.

What you’ll do

Partner with analysts, data engineers and business teams to design, build and maintain scalable data models that power reliable insights, experimentation and performance tracking.

Work alongside Clinical AI, LLMOps and Applied AI engineers to bring evaluations and LLM-powered data enrichment into production.

Develop and manage data pipelines across our regional workspaces on AWS and Azure, with accuracy, consistency and trust built in.

Use strong SQL and analytical thinking to turn complex data into clear, usable structures for analysis and reporting.

Design product event tracking with engineers so new features ship with data the business can trust.

Contribute to customer-facing data products, such as the Heidi analytical API and data shares with health systems, and make sure data is accurate, accessible and PHI-safe.

Improve access to data so teams can self-serve insights, from Omni dashboards to reverse ETL into tools like Braze and HubSpot.

Champion data quality, testing, documentation and governance across all analytics workflows.

Contribute to shared practices, frameworks and AI-assisted tooling that make analytics more efficient, consistent and scalable.

What we're looking for

3–5 years of experience in analytics engineering, data engineering or a similar data-focused role in a fast-paced or high-growth environment.

Strong proficiency in SQL and experience transforming data for analysis, reporting and product use cases.

Working knowledge of Python and PySpark.

Experience with modern data platforms and workflows, ideally including dbt, Databricks, Airflow, Snowplow, and reverse ETL or BI tools such as Omni.

A solid understanding of data modelling, data quality and testing best practices.

Ability to work with analysts, engineers, AI teams and business stakeholders to translate data needs into scalable, reliable solutions.

Interest in AI and LLM workloads, such as evaluations or model-based enrichment, and an appetite to go deeper alongside AI engineers.

Experience supporting or developing customer-facing data products, and care in handling sensitive health data such as PHI and PII.

Strong communication skills and a focus on clarity, documentation and long-term maintainability.

Curiosity, accountability and a drive to improve how data is built, managed and used across the business.

How we show up

Build for the next decade, not next quarter. Our targets are outrageous on purpose. The world's health doesn't have the luxury of incrementalism.

Lead, don't wait. We treat tomorrow's problems today. Sometimes we build what's needed before it's wanted, and we're fine with that.

Follow the evidence. Trust the patient. We pursue truth relentlessly. But when the subjective and objective disagree, we treat the patient, not the numbers. Ego is a comorbidity we can't afford.

Own the outcome. Everyone here carries the company. Raise problems with solutions, solve them end-to-end, and never be a bystander.

Ship, measure, go again. A button today, a workflow tomorrow. More iterations beat better planning. We're precise at pace, not reckless.

Live in clinicians' reality. Not the ideal workflow, the twenty-patients-before-lunch actual one. We build for exhausted humans, and we'd better be decent ones while we do it.

Why Heidi?

You’ll join a team measured on real-world impact, not press cycles. We live and breathe the challenges of modern health systems, and are laser-focused on exacting the change we’d like to see. We’re medicos, engineers, builders and designers who’ve felt (on every side of the equation) what non-care feels like, the moral and practical toll as a provider or receiver.

Building what we’re building isn’t always easy. Standard tech playbooks routinely fail in healthcare, and the friction of the medical system will test your perseverance. But we didn’t choose easy, we chose a purpose-driven mission that actually matters. We hold ourselves to a higher standard because healthcare demands it. If you join Heidi, you recognize that the deeper question isn’t whether AI can solve the global healthcare crisis, but whose hands will shape it.

True A-players progress extremely fast here. The nature of the scale-up game is demanding, but we value sustainable performance and mental health. You're trusted to perform, and you set your schedule. We operate on outcomes > inputs, not process theatre. We all take the bins out, metaphorically and literally.

We offer a $1,000 annual learning and development budget, a $150/month health and wellness allowance, a $500 home office budget, 26 weeks paid primary parental leave and 18 weeks paid secondary parental leave, fertility support up to $10,000, four weeks of work from anywhere per year, and serious equity.

We chose to open-source our benefits hub, if you care to take a peek.