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# Data Engineer

- **Company:** Network Plus
- **Location:** Tyldesley, UK
- **Contract:** Permanent contract
- **Skills:** Business Analytics Applications, Business Intelligence Development, Cloud Engineering, Data Architecture, Data Governance, Extract Transform Load (ETL), Data Warehousing, Python (Programming Language), SQL Azure, Power BI, DataOps, SQL Databases, Enterprise Data Management, Azure Data Factory, Microsoft Fabric, Data Lakes, Pyspark
- **Published:** July 19, 2026
- **Apply:** https://uk.indeed.com/viewjob?jk=9121f7d03df60ed2

## About the Role

* Proven experience as a Data Engineer in a modern cloud-based data environment.
 * Strong experience with Microsoft Fabric and/or Azure Data Services, including Data Lake Storage, Data Factory, Azure SQL, and Synapse technologies.
 * Experience designing and supporting enterprise data warehouses and lakehouse architectures.
 * Proficiency in SQL, Python, PySpark, and data engineering best practices.
 * Strong understanding of ETL/ELT development, data modelling, and dimensional modelling techniques.
 * Experience with Power BI semantic models and analytics platforms.
 * Knowledge of data governance, security, and access control principles.
 * Excellent problem-solving, communication, and stakeholder management skills.
 * Experience working in Agile delivery environments is desirable.

## Description

* Design, develop, and maintain data pipelines, lakehouses, and warehouse solutions within Microsoft Fabric.
 * Support the ongoing migration and modernisation of legacy on-premises data warehouse and reporting solutions.
 * Develop and optimise ETL/ELT processes using Fabric Data Factory, Notebooks, PySpark, SQL, and related technologies.
 * Collaborate with Data Analysts, BI Developers, and business stakeholders to understand and deliver data requirements.
 * Implement and maintain data quality, governance, security, and monitoring processes.
 * Optimise platform performance, data models, and storage strategies to maximise efficiency and scalability.
 * Support semantic models and reporting solutions that enable self-service analytics across the organisation.
 * Troubleshoot and resolve data platform issues while continuously improving operational reliability.
 * Contribute to data architecture standards, best practices, and technical documentation.


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