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Senior Analytics Engineer

Sydney, New South Wales, Australia

Live, first seen by us 20 days ago
Pay
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Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
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Employment
Full-time — employment source
Employment type in the employer’s posting: FullTime
From the employer’s posting

What you’ll work on

Full posting
  • Design and maintain scalable data models for insights, experimentation and performance tracking

  • Develop and manage data pipelines across AWS and Azure workspaces

  • Design product event tracking with engineers for new features

  • Contribute to customer-facing data products such as the analytical API and health system data shares

  • Improve self-serve data access through Omni dashboards and reverse ETL

From the employer’s posting
design, build and maintain scalable data models that power reliable insights, experimentation and performance tracking
Develop and manage data pipelines across our regional workspaces on AWS and Azure
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
Improve access to data so teams can self-serve insights, from Omni dashboards to reverse ETL into tools like Braze and HubSpot
Apply at Heidi Health

Posting record

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Status in our records
Live
First seen by us
Oct 15, 202620 days ago
Recorded sightings
22
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 20

Similar jobs usually come down between day 6 and day 47.

From 1,409 similar postings that came down. Coming down is not always a hire.

Heidi Health is hiring

1 open job

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Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • Azure
  • Databricks
  • dbt
  • Airflow
  • PySpark
Where the posting names them
- 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.
- 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.
- 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.
- 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.
- 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.

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About the role

We file this job under Analytics Engineer, by the work the posting describes.

Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.

Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.

A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

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.

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Sydney, New South Wales, Australia

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