Senior Data Engineer (Microsoft Fabric, PySpark, SQL)

Job Description

See yourself in our team

You’ll join a collaborative, Sydney-based team working across data engineering, analytics and business stakeholders. Your focus will be to design, build and improve scalable data solutions that turn complex source data into trusted, analytics-ready products.

• Design and build data ingestion and transformation workloads in Microsoft Fabric using PySpark and advanced SQL.
• Apply medallion architecture principles across Bronze, Silver and Gold layers to create governed, reusable data products.
• Connect to and ingest data from APIs, web services, relational databases, files, cloud storage and event-based sources.
• Design analytics-friendly data models, including facts, dimensions and curated datasets.
• Implement data quality checks, reconciliation controls, validation, monitoring and robust error handling.
• Translate business and technical requirements into data models, business rules and practical engineering solutions.
• Use source control, automated testing, continuous integration and delivery practices, and clear technical documentation.
• Collaborate with engineers, analysts, BI developers, architects and stakeholders in an Agile delivery environment.

We’re interested in hearing from people who:

Bring strong hands-on data engineering experience and can work confidently across design, development, troubleshooting and optimisation. You’ll combine technical depth with sound judgement, clear documentation and a collaborative approach.

• Have strong hands-on experience with Microsoft Fabric, PySpark and advanced SQL.
• Have extensive experience applying medallion architecture to enterprise data solutions.
• Can develop and troubleshoot scalable ingestion, transformation and API-based integration patterns across multiple environments.
• Understand data modelling, data lineage, metadata management, data quality and reconciliation controls.
• Use generative AI and coding-assistant tools responsibly, including model selection, prompt and context design, cost awareness, output evaluation, security and human review.
• Are familiar with Git, automated testing, continuous integration and delivery, and release management for data engineering solutions.
• Can gather requirements and translate them into durable data models, rules and engineering outcomes.
• Experience with T-SQL and dynamic SQL is desirable

Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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