Data Engineer

Role overview

What you’ll do

• Build and maintain reliable pipelines and curated datasets for reporting, analytics, and AI initiatives.
• Design dimensional, semantic, and other analytical models.
• Develop reusable transformations using Python, SQL, dbt, and Apache Airflow.
• Improve data quality with automated testing, monitoring, documentation, and lineage.
• Optimize queries and solutions for performance, scalability, and cost.
• Translate business requirements into maintainable data products.
• Partner with BI, data science, analytics, architecture, and product teams.
• Contribute to peer reviews, technical discussions, and shared engineering standards.
• Help establish consistent business definitions while balancing governance and delivery pace.

What you’ll need

• Around five or more years of data engineering experience or comparable practical experience.
• Strong hands-on capability with Python, SQL, dbt, and Apache Airflow.
• Experience building data pipelines and analytical solutions on cloud platforms such as Snowflake.
• Knowledge of dimensional modelling, Data Vault, or other contemporary modelling approaches.
• Experience developing semantic layers and business-friendly data structures.
• Understanding of data governance, quality, lineage, and metadata principles.
• Familiarity with source control, CI/CD, automated testing, and engineering practices.
• Experience in Agile, cross-functional product teams.
• Relevant qualification or equivalent industry experience.
• Power BI, retail data, machine learning, or AI-enabled analytics exposure is useful but not essential.

Benefits

• Benefits listed include team discounts, OnePass membership, team member benefits, and 12 weeks of paid parental leave regardless of gender.
• The employer describes career development, learning opportunities, and a collaborative team environment.

About Bunnings