Design, build and maintain data engineering solutions in SQL and Python on Enterprise Data Platforms
Develop and sustain data pipelines that move data from source to consumption reliably and at scale
Operationalise data so it is accessible, trusted and ready for use by business areas
Fuse data from multiple sources using transformation, integration, normalisation and feature extraction techniques
Create data structures that support downstream analytics, reporting and decision making
Apply appropriate tools and techniques across the end-to-end data management lifecycle in line with agreed process standards and industry-specific regulations
Build standardised tooling and techniques that drive consistency in ETL and data warehousing approaches across the team
Carry out data quality checking and remediation to maintain confidence in the data
Produce clear technical documentation and track work using collaboration tools
Work in a diverse team environment, sharing outcomes and experience to support the development and growth of others
Engage with technical and business stakeholders to understand data needs and deliver fit-for-purpose solutions
Requirements
You must hold a current PV security clearance and be an Australian citizen to be considered for this role
3+ years' relevant Data Engineering or Data Warehousing experience, with strong hands-on skills in SQL and Python
Proven ability to develop, deploy and maintain scalable ETL pipelines and data engineering solutions on Enterprise Data Platforms
Experience fusing data sources using transformation, integration, normalisation and feature extraction to create useful data structures
Track record of building standardised tooling, applying rigorous data quality assurance and remediation, and producing clear technical documentation