Data Engineer AU IT Hybrid

What Were Looking For

Must-Have Skills

• 2+ years of hands-on data engineering experience across Microsoft Fabric and legacy SQL Server environments
• Strong SQL skills for complex data transformation and performance optimization
• Experience building end-to-end data pipelines using Microsoft Fabric tools (Data Factory, Synapse, Notebooks)
• Python or PySpark experience for data processing and transformation
• Solid understanding of ETL/ELT patterns across modern cloud and legacy systems
• Experience creating analytics-ready gold tables and semantic models in collaboration with Data Analysts
• Performance tuning experience across Fabric compute engines and traditional SQL Server platforms
• Integration experience with legacy technologies including SSIS, SSRS, and cube processing
• Ability to collaborate closely with analysts, business stakeholders, and external vendors
• Strong troubleshooting and problem-solving skills for pipeline and data quality issues
  
  

Nice-to-Haves

• Microsoft Fabric or Azure certifications (DP-600, DP-203)
• Experience with Git-based version control and CI/CD for data pipelines
• Exposure to real-time or streaming data processing technologies
• Background in business intelligence or analytics engineering
• Experience implementing data quality frameworks, monitoring, or alerting solutions
  
  

What Youll Do

As a Data Engineer within the Data & Analytics team, you will design, build, and optimize reliable data pipelines and transformation processes using Microsoft Fabric. You will work closely with Data Analysts to deliver high-quality gold tables for analytics, while supporting both legacy environments and vendor-led data initiatives.

Key Responsibilities

Pipeline Development & Integration

• Design and build end-to-end data pipelines using Microsoft Fabric tools including Data Factory, Synapse, and Notebooks
• Develop robust ETL/ELT processes for ingesting data from modern cloud and legacy source systems
• Create, optimize, and maintain gold tables and semantic models for analytics consumption
• Implement batch and real-time data processing solutions with a focus on scalability and performance
• Build automated data validation and quality assurance processes across Fabric and legacy platforms
• Manage integrations with legacy SQL Server environments including SSIS packages and cube processing
  
  

Data Transformation & Performance Optimization

• Transform raw data into analytics-ready structures following dimensional modelling best practices
• Implement complex business logic and calculations within Fabric-based pipelines
• Develop reusable data assets and standardized metrics in partnership with Data Analysts
• Optimize query and pipeline performance across Fabric compute engines and SQL Server systems
• Implement incremental loading strategies and tuning for large datasets
• Monitor and manage data performance across both modern and legacy environments
  
  

Business Collaboration & Vendor Support

• Partner with Data Analysts and business stakeholders to understand reporting and analytics requirements
• Provide technical guidance to external vendors during data product build phases
• Ensure vendor-delivered pipelines meet integration, performance, and architectural standards
• Collaborate on data model design supporting both BAU reporting and new analytical use cases
• Support legacy reporting environments including Excel, SSRS, and Power BI where required
• Investigate and resolve data quality issues across internal and vendor-built solutions
  
  

Quality Assurance & Monitoring

• Write and maintain unit and integration tests for data pipelines
• Implement data quality monitoring, alerting, and failure detection mechanisms
• Troubleshoot pipeline failures, performance issues, and data inconsistencies
• Maintain technical documentation, pipeline designs, and operational runbooks
• Support deployment, release, and change management processes
  
  

Why Join Us

• Opportunity to work with Microsoft Fabric and enterprise-scale data platforms
• Exposure to both modern cloud data engineering and legacy enterprise environments
• High-impact role building core data assets that power analytics and decision-making
• Collaborative squad-based delivery model with strong analyst and platform partnerships
• Professional development support including Microsoft certification pathways
• Hands-on involvement in vendor-led data product builds and modernization initiatives
  
  

About The Team

You will join a small, highly autonomous Data & Analytics squad operating within an agile framework. The team works closely with business stakeholders, analysts, platform engineers, and external vendors to deliver scalable, reliable, and high-performing data solutions.

Position Impact & Collaboration

• No direct reports, but significant technical ownership and influence across the data platform
• Works closely with Data Analysts to enable trusted, analytics-ready data assets
• Collaborates with Data Platform Engineers on architectural alignment and platform standards
• Acts as a key technical contact for vendor delivery and pipeline implementation
• Supports legacy-to-modern data migration initiatives
  
  

Success Measures

• Reliability, performance, and scalability of data pipelines
• Accuracy and usability of gold tables and analytics-ready datasets
• Reduction in data quality incidents and pipeline failures
• Successful delivery of vendor-built data products aligned to standards
• Progression of legacy system migration and platform modernization

---