Staff Data Engineer

Summary

Join Heidi Health as a Staff Data Engineer and become a key technical leader responsible for designing, implementing, and evolving our data infrastructure and architecture. Build reliable, scalable, and secure data systems that power our core products and AI functions. Lead the design and implementation of a scalable data lakehouse architecture on AWS. Architect and build robust ELT pipelines using technologies like S3, Athena, Lake Formation, Trino, and Databricks. Own the orchestration strategy using tools like Airflow, Databricks Workflows, or Dagster. Collaborate with Machine Learning Engineers to optimize data platforms for model training, deployment, and monitoring. Drive technical decisions on data tooling, architecture, and engineering best practices. Embed data privacy, security, and compliance controls. Provide technical leadership and mentorship to engineers. Promote a culture of documentation, testing, and operational rigor. Heidi offers a flexible hybrid working environment, additional paid time off, corporate fitness rates, a personal development budget, equity in the company, and the chance to make a global impact.

Requirements

• A minimum of 5+ years of experience in data engineering or a related field
• Proven track record of building and scaling production data systems in cloud environments (preferably AWS and Databricks)
• Expertise in designing and implementing robust data pipelines, ETL processes, and data warehouses
• Demonstrable experience providing direct data engineering support to Machine Learning teams, including data preparation, feature engineering, and model deployment

Responsibilities

• Lead the design and implementation of a scalable, secure, and highly available data lakehouse architecture on AWS to support our product and AI teams
• Architect and build robust, production-grade ELT pipelines leveraging technologies such as S3, Athena, Lake Formation, Trino, and Databricks (preferred)
• Own orchestration strategy using tools like Airflow, Databricks Workflows, or Dagster to manage complex, dependency-driven workflows
• Work closely with Machine Learning Engineers to deliver data platforms optimised for model training, deployment, and monitoring
• Drive technical decisions on data tooling, architecture, and engineering best practices—balancing innovation with long-term maintainability and cost-effectiveness
• Embed data privacy, security, and compliance controls aligned with healthcare and industry standards such as HIPAA, SOC 2, and ISO 27001
• Provide technical leadership and mentorship to engineers across the organisation, raising the bar for excellence in data engineering and cross-functional delivery
• Promote a culture of documentation, testing, observability, and operational rigour across all data systems

Benefits

• Flexible hybrid working environment, with 3 days in the office
• Additional paid day off for your birthday and wellness days
• Special corporate rates at Anytime Fitness in Melbourne, Sydney tbc
• A generous personal development budget of $500 per annum
• Learn from some of the best engineers and creatives, joining a diverse team
• Become an owner, with shares (equity) in the company, if Heidi wins, we all win
• The rare chance to create a global impact as you immerse yourself in one of Australia’s leading healthtech startups
• If you have an impact quickly, the opportunity to fast track your startup career!