Help shape our next data platform.
- We’re modernising our data platform and looking for an experienced Data Engineer to help build it.
- You’ll work with analysts, data scientists and business teams to build reliable pipelines, develop well-structured data models and make data easier to use across the business.
- We’re moving from legacy systems to a cloud-native stack using Estuary, dbt, Google Cloud Platform (GCP) and Snowflake. There’s plenty to work through, and you’ll have a say in the architecture, tools and engineering practices we put in place.
- If you enjoy getting into the detail, solving problems and seeing your work put to use, we’d like to hear from you.
What you’ll work on
- Design and build scalable ELT pipelines that bring together data from multiple sources.
- Develop and maintain data models using dbt.
- Optimise Snowflake models and workloads for performance and cost.
- Turn raw data into reliable datasets for reporting and advanced analytics.
- Build in data quality checks, monitoring and alerts so issues are picked up early.
- Help plan and deliver the migration from legacy systems to the new platform.
- Apply sound engineering practices, including testing, CI/CD and code reviews.
- Work with technical and business teams to understand what they need and deliver practical solutions.
- Contribute to documentation and engineering standards, and support junior engineers as they develop.
Requirements
What you’ll need
- A relevant tertiary qualification: a diploma or bachelor’s degree in Computer Science, Information Technology, Information Systems, Data Engineering or a closely related field.
- At least four years’ experience in data engineering or a similar role.
- Strong SQL skills, including experience with complex transformations and query optimisation.
- Proficiency in Python or a similar language for data processing and automation.
- Experience building ELT pipelines in a cloud environment such as AWS, Azure or GCP.
- Hands-on experience with a modern data warehouse such as Snowflake or Azure Synapse.
- Experience using data transformation or orchestration tools such as dbt, Airflow or Dagster.
- Experience working with structured and semi-structured data, including JSON and Parquet.
- A sound understanding of data governance, security and data quality practices.
- You should be comfortable taking responsibility for your work, explaining technical decisions and working through problems with people across the business.
Experience that would be useful
- Estuary or other data integration and change data capture tools.
- Streaming technologies such as Kafka or Spark Streaming.
- BI tools such as Qlik, Power BI, Looker or Tableau.
- Qlik Replicate, Qlik Compose or similar tools.
- Agile delivery using Jira or Azure DevOps.
- DevOps practices or relevant cloud, Snowflake or dbt certifications.
What makes this role interesting
- You’ll join a growing data function at a point where your experience can help shape how the platform develops. Alongside building pipelines and models, you’ll contribute to architecture decisions, establish working practices and mentor junior engineers.
- It’s an opportunity to work with a modern stack and see the effect of your work across the business.