Data Engineer

Role Overview

Support Data Platform and AI across service groups and squads by providing data engineering capability that aligns with quarterly planning priorities. Contribute to solving business and customer problems through effective use of data.

What You Will Do

Build, productionise, and maintain data pipelines, predictive models, and customer value calculations. Test, review, and revise code to ensure quality, reliability, and maintainability.

Why It Might Be a Fit

At least 3+ years’ experience in software or data engineering within a corporate environment. Strong proficiency in Python for data pipeline development and refactoring.

Requirements

• At least 3+ years’ experience in software or data engineering within a corporate environment
• Strong proficiency in Python for data pipeline development and refactoring
• Working knowledge of PySpark and Scala for data ingestion and processing
• Solid SQL skills for source and staging layers
• Exposure to Hadoop ecosystem, including HDFS and open-source data technologies
• Experience using Terraform is advantageous
• Hands-on experience with Apache Airflow as an orchestrator for data ingestion and validation
• Understanding of data lake architectures, including secure and reliable ingestion patterns
• Familiarity with Snowflake and integration with upstream/downstream systems
• Strong understanding of modularisation and reusable design patterns
• Involvement in end‐to‐end CI/CD workflows for Airflow and data platform codebases
• Strong testing mindset with experience in Unit testing, Integration testing, Regression testing
• Experience working with cloud platforms, preferrable AWS

Benefits

• 4 weeks standard holiday + 5 additional days of wellbeing leave
• Additional purchased leave options up to 4 weeks per year
• Banking benefits, insurance discounts and superannuation scheme
• Growth and development
• Recognition
• School holiday subsidy
• 2 Volunteer days per year