Data Engineer (AU Client - Project Based | Remote)

You will be required to assist in the design, development, and maintenance of scalable data solutions across internal reporting, analytics, and business intelligence systems.

Managing data pipelines, integrating data from multiple business platforms, and ensuring data is accurately transformed, structured, and maintained to support operational and strategic reporting requirements.

Other responsibilities include but are not limited to:

• Design, develop, and maintain scalable data pipelines using Microsoft Fabric, Azure Data Factory, and related Azure services.
• Ingest, transform, and integrate data from platforms including HubSpot, Manatal, SharePoint, APIs, databases, and flat files.
• Build and optimise data models to support reporting, analytics, and Power BI dashboards.
• Develop reusable ETL/ELT processes to support business intelligence and operational reporting requirements.
• Support the development and maintenance of data warehouses, lakehouses, and semantic models within Microsoft Fabric.
• Monitor, troubleshoot, and optimise data pipeline performance and data transformation processes.
• Ensure data quality, accuracy, consistency, and reliability across source systems and reporting layers.
• Document data flows, transformations, integration logic, and technical processes.
• Collaborate with stakeholders, analysts, and BI developers to understand reporting and data requirements.
• Assist in maintaining secure, organised, and scalable data environments across cloud-based platforms.

• Proven experience in data engineering, ETL/ELT development, and data pipeline design.
• Required hands-on experience with Microsoft Fabric, including Lakehouse, Warehouse, Dataflows, Pipelines, or Notebooks.
• Strong experience with Azure Data Factory and Azure-based data services.
• Experience integrating data from business platforms such as HubSpot, Manatal, and SharePoint.
• Strong understanding of data modelling concepts, including star schema, fact and dimension tables, and semantic models.
• Proficiency in SQL and data transformation processes.
• Experience working with APIs, connectors, JSON, CSV, Excel, and relational databases.
• Familiarity with Power BI data models and reporting requirements.
• Experience with cloud-based data platforms and modern data architecture practices.
• Exposure to Python or PySpark for data transformation is beneficial.
• Strong troubleshooting, analytical, and problem-solving skills.
• Strong documentation, organisational, and communication skills.
• Ability to work independently and collaboratively within cross-functional teams.