Microsoft Fabric Developer / Data Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 51d ago
The date the source published, not the day we noticed it (2026-09-12). Last seen at its source just now.
We have tracked this listing since 17 Oct 2026 (15 days). The employer's own board has carried it every time we have read it, most recently just now.
Is it remote?
Remote
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Who may apply?
Not stated
The description states no restriction of its own. This is the source's own tag.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
JazzHR employer's own board first seen 15d ago · last seen just now
The listing
Microsoft Fabric Developer / Data Engineer
Experience: 3+ Years
Role Type: Full-Time
Primary Technology: Microsoft Fabric / Azure Data Platform
Role Overview
We are looking for a hands-on Microsoft Fabric Developer / Data Engineer with 3+ years of experience in data engineering and Azure-based data solutions. The candidate will be responsible for designing, developing, and maintaining scalable data pipelines and modern data solutions using Microsoft Fabric, OneLake, Lakehouse, Data Warehouse, Fabric Data Factory, Python/PySpark and SQL.
The ideal candidate should have practical experience building end-to-end data solutions, integrating multiple enterprise data sources, and supporting analytics and reporting workloads.
Key Responsibilities
- Design, develop and maintain data solutions using Microsoft Fabric.
- Build and manage Fabric Lakehouse, Data Warehouse and OneLake solutions.
- Develop scalable ETL/ELT pipelines using Fabric Data Factory, Data Pipelines and Dataflows Gen2.
- Develop data transformation and processing workflows using Python, PySpark, SQL and Fabric Notebooks.
- Ingest and integrate data from databases, APIs, files, Azure services and other enterprise systems.
- Implement Lakehouse/Medallion architecture including Bronze, Silver and Gold data layers.
- Design and optimize data models for analytics, reporting and downstream applications.
- Optimize SQL queries, Spark workloads and pipelines for performance and scalability.
- Implement data validation, quality checks, monitoring, logging and error handling.
- Work with development, analytics and business teams to translate requirements into scalable technical solutions.
- Support deployment and CI/CD processes for Microsoft Fabric workloads.
Required Technical Skills
- 3+ years of Data Engineering / Azure Data Platform experience
- Strong hands-on experience with Microsoft Fabric
- Fabric Data Factory, Pipelines and Dataflows Gen2
- OneLake and Fabric Lakehouse
- Fabric Data Warehouse
- Fabric Notebooks
- Strong SQL / T-SQL
- Python and PySpark
- ETL/ELT and data pipeline development
- Data warehousing and data modelling
- Azure ecosystem such as Azure Data Factory, Azure SQL, ADLS and/or Azure Synapse
- Experience integrating REST APIs and multiple enterprise data sources
- Understanding of Delta Lake and Medallion Architecture
- Git/Azure DevOps and CI/CD fundamentals
Good to Have
- Power BI, DAX, Semantic Models and Direct Lake
- Real-time analytics or streaming experience
- Azure OpenAI or other AI/ML integration experience
- Experience supporting enterprise-scale data platforms
- Data governance, security and access-control experience
- Microsoft DP-600 / Fabric Analytics Engineer or related Azure certification
Preferred Candidate
We are looking for someone who has actually built and deployed Microsoft Fabric solutions, rather than having only certification or theoretical exposure. The candidate should be comfortable explaining the architecture, pipelines, transformations and Fabric components they personally implemented in previous projects.