Summary
✨ AI‑Generated
Join a collaborative data team as a hands-on Data Engineer, building and maintaining pipelines that support reporting, analytics, and business initiatives. You will work with SQL, Azure Data Factory, and Databricks while contributing to data quality, documentation, and continuous improvement.
Highlights
Hands-on data engineering role with exposure to the modern Azure data stack and Databricks, supported by a collaborative data team and opportunities to grow while working on reporting, analytics, and business initiatives.
Description
About The Role
We're looking for a hands-on Data Engineer with 3 to 5 years of experience to join the Accent Data team.
This role blends delivery, support and learning, where you'll work closely with the wider data team to build and maintain the pipelines that power reporting, analytics and business initiatives across the group.
You'll cover the modern Azure data stack through to Databricks while working alongside a strong data team who'll support your growth in a fast-paced retail environment.
Write and optimise SQL to validate, shape and troubleshoot data across pipelines and data martsBuild, test and maintain data pipelines in Azure Data Factory to move and transform data across source systems and support company initiativesAbility to process and transform data within Databricks using notebooks, build basic data pipelines, manage storage, and navigate core features like Unity CatalogContribute to data quality and documentation practices across the data landscapeLearn from and collaborate with senior members of the data team, growing your skills across the Azure data platform
To Be Successful You Will Have
Strong proficiency in Microsoft SQL Server or Azure SQL Database, including writing, troubleshooting, and optimizing queries and stored proceduresExperience building and optimising ETL/ELT pipelines using Azure Data Factory, with broader exposure to Azure cloud data platformsWorking knowledge of Python for data engineering tasks or programming foundation in language other than SQLWorking with Databricks for data processing and transformation, including using notebooks, understanding key architecture concepts, and working with Unity CatalogAbility to work in a fast-paced environment and manage competing prioritiesGood communication skills and comfort working closely with a data teamExperience in retail, or interest in retail data (trading, inventory, customer performance), is a plus but not essential
What We're Looking For
A hands-on, pragmatic problem solver who enjoys getting into the detailSomeone eager to learn, take feedback well, and grow into a stronger data engineerComfortable working as part of a team, asking questions, and building autonomy over timeA curious mindset with an interest in new tools, technologies and better ways of working
Accent Group is one of Australia and New Zealand's leading retail groups.
Our portfolio includes some of the world's most recognisable footwear and lifestyle brands, including Platypus, Hype DC, The Athlete's Foot, Skechers, Vans, Subtype and Lacoste.
We’re powered by innovation, collaboration, and a deep love for our brands and we’re looking for people who share that same drive.
Benefits
A dynamic and collaborative Support Office environment Generous employee discounts across our extensive brand portfolio Opportunities for career development and progression The chance to work with some of the most recognised brands in Australian retail A culture that encourages innovation, ownership and new ideas
At Accent Group Limited we are committed to creating an inclusive workplace that promotes and values diversity and inclusion.
We believe in the diversity of our people across age, gender, identity, race, sexual orientation, ethnicity, physical and mental ability.
We strive on creating an equal employment environment where everyone from any background can be themselves.
The Accent Group acknowledges, and pays respect, to the Traditional Owners and ongoing custodians of the land.
The Aboriginal and Torres Strait Islander and Maori people.