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Open nowFirst seen 14 hours ago

Data Engineer MS Fabrics

Thehrally Com65 open roles

Where
Sydney, New South Wales, Australia
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Your applicationOpen nowData Engineer MS FabricsThehrally Com · Sydney, New South Wales, Australia

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Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
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  2. 4.3%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: first seen 14 hours ago

The posting

Role: MS Fabric Data Engineer

Location: Sydney

Job Type: Permanent

Experience: 5+ yrs

Job Description:

Roles and Responsibilities:

  • Design, build, and maintain end-to-end data pipelines using Microsoft Fabric Data Engineering and Data Factory.
  • Develop and manage Lakehouse and One Lake architectures for structured and unstructured data.
  • Ingest data from multiple sources (databases, APIs, files, streaming sources) into Fabric.
  • Implement ETL/ELT processes using Spark (Pyspark) and SQL.
  • Design and optimize data models to support analytics and reporting workloads.
  • Develop and maintain Fabric Data Warehouse solutions using T-SQL.
  • Ensure data quality, reliability, and consistency through validation and monitoring.
  • Optimize pipeline performance, storage, and capacity utilization in Fabric.
  • Implement security, access control (RBAC), and data sensitivity labels.
  • Enable and support Power BI semantic models and downstream reporting use cases.
  • Monitor, troubleshoot, and resolve data pipeline and performance issues.
  • Implement data governance, lineage, and cataloguing using Microsoft Purview.
  • Support CI/CD and DevOps practices for analytics and data engineering workloads.
  • Collaborate with architects, analysts, and stakeholders to translate business requirements into scalable data solutions.

Skill Experience requirement:

  • Design enterprise data architecture leveraging Fabric components (Lakehouse, Warehouse, Dataflows Gen2, Pipelines, OneLake).
  • Build and optimise Fabric Lakehouse tables, Warehouses, Pipelines, and Dataflows Gen2.
  • Define data modelling standards, governance frameworks, and security patterns.
  • Develop reusable ETL/ELT frameworks using PySpark, SQL, and Fabric notebooks.
  • Manage CI/CD workflows via Azure DevOps and Git.
  • Architect scalable, cost-efficient data solutions integrating Fabric with Azure/enterprise systems.
  • Apply best practices for performance tuning, cost optimisation, and data quality.
  • Provide technical leadership and guidance to engineering teams.
  • Expertise in Delta Lake, Fabric Data Engineering, ADLS, PySpark/SQL.
  • Strong understanding of data modelling and integration with Power BI datasets.
  • Strong understanding of metadata management, Purview, access control, and FinOps.
  • Certifications: DP-203, Fabric Analytics Engineer (preferred).

· Design, build, and maintain end-to-end data pipelines using Microsoft Fabric Data Engineering and Data Factory.

· Develop and manage Lakehouse and OneLake architectures for structured and unstructured data.

· Ingest data from multiple sources (databases, APIs, files, streaming sources) into Fabric.

· Implement ETL/ELT processes using Spark (PySpark) and SQL.

· Design and optimize data models to support analytics and reporting workloads.

· Develop and maintain Fabric Data Warehouse solutions using T-SQL.

· Ensure data quality, reliability, and consistency through validation and monitoring.

· Optimize pipeline performance, storage, and capacity utilization in Fabric.

· Implement security, access control (RBAC), and data sensitivity labels.

· Enable and support Power BI semantic models and downstream reporting use cases.

· Monitor, troubleshoot, and resolve data pipeline and performance issues.

· Implement data governance, lineage, and cataloging using Microsoft Purview.

· Support CI/CD and DevOps practices for analytics and data engineering workloads.

· Collaborate with architects, analysts, and stakeholders to translate business requirements into scalable data solutions.

Skill Experience requirement :

· Design enterprise data architecture leveraging Fabric components (Lakehouse, Warehouse, Dataflows Gen2, Pipelines, OneLake).

· Build and optimise Fabric Lakehouse tables, Warehouses, Pipelines, and Dataflows Gen2.

· Define data modelling standards, governance frameworks, and security patterns.

· Develop reusable ETL/ELT frameworks using PySpark, SQL, and Fabric notebooks.

· Manage CI/CD workflows via Azure DevOps and Git.

· Architect scalable, cost-efficient data solutions integrating Fabric with Azure/enterprise systems.

· Apply best practices for performance tuning, cost optimisation, and data quality.

· Provide technical leadership and guidance to engineering teams.

· Expertise in Delta Lake, Fabric Data Engineering, ADLS, PySpark/SQL.

· Strong understanding of data modelling and integration with Power BI datasets.

· Strong understanding of metadata management, Purview, access control, and FinOps.

· Certifications: DP-203, Fabric Analytics Engineer (preferred).

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