Senior Analytics Engineer — AI-Powered Health Data

Alt; Sydney, Melbourne; Remote; AUD 120,000 - 180,000; Full time

Benefits offered by this job

Learning budget

Wellness allowance

Home office budget

Parental leave (26 weeks)

Fertility support

Work from anywhere 4 weeks/year

Equity

Job summary

Heidi is building the future of healthcare with a focus on trustworthy AI-powered data products. This analytics engineering role partners with analysts, data engineers and clinicians to deliver scalable data models and reliable insights across healthcare domains.

You will design production data pipelines on AWS/Azure, apply SQL/Python skills, and contribute to customer-facing data products while ensuring data quality and PHI safety. The team values bold experimentation and clear documentation.

Qualifications

• 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.

Responsibilities

• 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.

Skills

SQL proficiency

Python

PySpark

Data modeling

Communication

Data quality

Collaboration

AI/LLM interest

Tools

dbt

Databricks

Airflow

Snowplow

Omni

Job description

Heidi is building the future of healthcare with a focus on trustworthy AI-powered data products. This analytics engineering role partners with analysts, data engineers and clinicians to deliver scalable data models and reliable insights across healthcare domains.

You will design production data pipelines on AWS/Azure, apply SQL/Python skills, and contribute to customer-facing data products while ensuring data quality and PHI safety. The team values bold experimentation and clear documentation.