Lead Microsoft Fabric Data Engineer - End-to-End Platform

Xceltium; Sydney; Hybrid; AUD 130,000 - 170,000; Full time

Job summary

Xceltium is seeking an experienced Data Fabric Engineer to lead the Microsoft Fabric initiative in Sydney. You will define the technical approach, design Lakehouse and Warehouse structures, and build robust ingestion and transformation pipelines.

This 12-month FTC offers hybrid working from Sydney CBD, with a clear path to hands-on impact, security governance, and cost-aware operations across Azure, Data Factory, SQL, Python/Spark.

Qualifications

• Experience building Microsoft Fabric environments.
• Design Fabric architecture, Lakehouse and Warehouse structures.
• Strong data ingestion, transformation and pipeline capability.
• SQL data modelling expertise.
• Experience with Python and/or Spark.
• Understanding of security, governance and data quality.
• Exposure to Azure and modern deployment practices including Git and CI/CD.
• Ability to translate complex source systems into practical technical designs.

Responsibilities

• Define the technical approach across the Fabric environment end-to-end.
• Design Lakehouse/Warehouse structures and engineering patterns.
• Build ingestion and transformation pipelines with reliable, cost-aware operation.
• Ensure security, governance, and data quality across workloads.
• Collaborate with leadership and translate requirements into designs for the platform.

Skills

Microsoft Fabric

Fabric architecture

Lakehouse/Warehouse

Ingestion & ETL pipelines

SQL data modelling

Python / Spark

Security & governance

Azure cloud

CI/CD practices

Tools

Git

Azure

Job description

Xceltium is seeking an experienced Data Fabric Engineer to lead the Microsoft Fabric initiative in Sydney. You will define the technical approach, design Lakehouse and Warehouse structures, and build robust ingestion and transformation pipelines.

This 12-month FTC offers hybrid working from Sydney CBD, with a clear path to hands-on impact, security governance, and cost-aware operations across Azure, Data Factory, SQL, Python/Spark.