$104,767 - $113,746 AUD yearly
The APS6 Data Engineer designs, builds and maintains trusted data products that make enterprise data easier to find, understand and use. Working as part of a multidisciplinary data team, the role transforms data from a range of source systems into well-structured, reliable and reusable datasets that support analytics, reporting and emerging AI use cases.
- Designs, develops and maintains assigned data pipelines and processes across the Azure Synapse-based data platform.
- Maintains assigned DevOps pipelines that automate the testing, deployment and release of data solutions across environments.
- Builds trusted, reusable data products using sound data engineering, testing and documentation practices.
- Escalate significant design, security, governance and delivery risks to the Lead Data Engineer.
- Works collaboratively with analytics engineers, analysts, business stakeholders and technology teams to translate data requirements into practical technical solutions.
- Contributes to established engineering standards, reusable patterns, technical documentation and continuous improvement across the data platform.
- Applies and promotes data governance practices in the development of data products, including data quality, documentation, lineage and appropriate use of data.
- Demonstrates technical capability in data engineering, such as Python, Spark, SQL, data modelling, transformation and the development of production data pipelines.
- Applies contemporary engineering practices such as version control, automated testing, CI/CD, documentation and code review.
- Experience with big data systems such as Azure Synapse, Databricks, Fabric or Snowflake.
- Develops high-quality solutions that consider data quality, security, governance, maintainability and performance throughout the data lifecycle.
- Analyses complex data and technical problems, exercises sound judgement and delivers practical solutions with limited direction.
- Communicates effectively with technical and non-technical stakeholders and contributes positively to a collaborative, multidisciplinary team.
- Demonstrates curiosity and initiative in using AI and emerging technologies to improve productivity, streamline data engineering processes and deliver more efficient solutions.