Data Engineer – 12-Month Fixed-Term Contract

- Location: Sydney | Hybrid
- Contract: 12-Month Fixed-Term Contract

The Opportunity

We’re looking for an experienced Data Engineer to join a growing Data & Insights team and help build out a modern data platform.

This is a hands-on role where you’ll be working across Snowflake, dbt and Azure, bringing together data from operational, ecommerce, marketing and legacy systems and turning it into reliable, analytics-ready datasets.

You’ll be joining at a point where the data environment is still being established, so there’s plenty of opportunity to influence how things are built, improve data quality and help shape the engineering standards used across the platform.

You’ll also have exposure to emerging AI and automation initiatives as the broader data capability continues to develop.

What You’ll Be Doing

- Build and maintain ELT pipelines from a range of source systems into Snowflake.
- Develop and maintain dbt models across a layered data architecture.
- Design dimensional models and reusable datasets for reporting, analytics and future AI use cases.
- Work with Azure Data Factory and ADLS for ingestion and orchestration.
- Investigate and resolve data quality issues including nulls, inconsistent keys and duplicate records.
- Develop approaches for master data management, entity resolution and customer matching.
- Build and maintain reference datasets, hierarchies, lookups and classification structures.
- Support Power BI reporting by providing well-structured and high-performing datasets.
- Configure and deliver iPaaS integrations between operational systems.
- Apply good engineering practices across Git, CI/CD, testing, code review and documentation.
- Work with data, reporting and business stakeholders to turn requirements into reliable data products.
- Contribute to data governance, data quality monitoring and platform standards as they continue to mature.




- Support AI and automation initiatives where relevant, including the integration of emerging AI tools and workflows.

What We’re Looking For

You’ll ideally have around 5–8 years of experience in data engineering and be comfortable working in a hands-on delivery environment.

We’re looking for experience across:

- Strong SQL and Python skills.
- Snowflake and dbt, including modelling, testing and documentation.
- Building and maintaining ELT pipelines.
- Master data management, entity resolution, customer matching or deduplication.
- Golden record design and deterministic or probabilistic matching approaches.
- Data quality profiling, validation and monitoring.
- Azure Data Factory and Azure Data Lake Storage.
- Hands-on delivery of iPaaS integrations.
- Dimensional modelling, star schemas and Kimball principles.
- Supporting BI platforms, ideally Power BI.
- Working with complex, inconsistent or legacy source systems.
- Git, CI/CD and agile delivery practices.
- Communicating clearly with both technical and non-technical stakeholders.

Nice to Have

- Experience in retail, ecommerce, distribution or other high-volume transactional environments.
- Exposure to ERP, PIM or operational management systems.
- Experience with AS400/iSeries or similar legacy platforms.
- Experience using Snowpark with Python.
- Exposure to tools such as ChatGPT, Claude, Gemini or Copilot.
- An interest in data governance, automation and emerging AI use cases.

Why This Role?

This is a good chance for someone who likes building rather than simply maintaining.

The platform is still evolving, the source systems are varied, and there’s a clear backlog of work to get through. You’ll have direct access to senior data leadership and the freedom to take ownership of your work without layers of unnecessary process.

If you enjoy working in a small team, solving messy data problems and building things properly from the ground up, this role should be worth a look.

📌 Data Engineer (Sydney)
🏢 SKL Technology
📍 Sydney