Job Overview
We are seeking a seasoned data engineer to lead our data infrastructure and architecture efforts.
This role will play a critical part in building reliable, scalable, and secure data systems that power core products and AI functions.
The ideal candidate will have a strong background in designing and implementing data pipelines, ETL processes, and data warehouses, as well as experience providing direct data engineering support to machine learning teams.
Key Responsibilities:
* Data Infrastructure Design: Design and implement a scalable, secure, and highly available data lakehouse architecture on AWS to support product and AI teams.
* Pipeline Architecture: Architect and build robust, production-grade ELT pipelines leveraging technologies such as S3, Athena, Lake Formation, Trino, and Databricks.
* Workflow Orchestration: Own orchestration strategy using tools like Airflow, Databricks Workflows, or Dagster to manage complex, dependency-driven workflows.
* Technical Leadership: Provide technical leadership and mentorship to engineers across the organisation, raising the bar for excellence in data engineering and cross-functional delivery.
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.
In addition to these key responsibilities, we also expect our ideal candidate to demonstrate expertise in data privacy, security, and compliance controls aligned with healthcare and industry standards.
We offer a collaborative and innovative work environment where you can grow your skills and make a real impact. If you're passionate about data engineering and want to join a team that values excellence and innovation, please submit your application.