Data Engineer: Fabric & Cloud Data Pipelines (Hybrid)

BRUSH careers

Loughborough

Híbrido

GBP 55.000 - 75.000

Jornada completa

14 días+

Una candidatura completa en un minuto

Currículum y carta de presentación personalizados, listos para enviar.

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Ventajas ofrecidas por este puesto de trabajo

Flexible/hybrid working options
Life insurance 4x annual salary
Enhanced company pension
Employee Assistance Programme
GP24 remote medical services
BRUSHRewards
Bike2work
Long service awards
Professional development

Descripción de la vacante

BRUSH Group in Loughborough is seeking a Data Engineer to design, build and operate robust data pipelines and platforms within the IT Data & AI team. You will connect source systems, apply the medallion architecture and deliver trusted data products using Microsoft Fabric, ensuring security, quality and governance.

You will collaborate with analysts and stakeholders to translate requirements into scalable data solutions, maintain data quality, and continuously improve deployment practices while

Formación

  • Degree or equivalent professional experience in data engineering, computer science, software engineering, mathematics or another relevant technical discipline.
  • Evidence of continued professional development in modern data engineering, cloud data platforms and development practices.
  • Microsoft certification, such as Fabric Analytics Engineer Associate, Azure Data Engineer Associate or an equivalent cloud data qualification. (desirable)
  • Strong SQL skills, including querying, transformation, optimisation and troubleshooting across complex datasets.
  • Practical knowledge of Microsoft Fabric, including Data Factory pipelines, Lakehouse, Warehouse, OneLake and notebooks.
  • Ability to design scalable data models and apply medallion architecture, dimensional modelling and reusable data-product principles.
  • Experience developing and maintaining a cloud-based lakehouse or data warehouse; Microsoft Fabric is strongly preferred.
  • Experience implementing data quality, monitoring, reconciliation, metadata, lineage and role-based access controls.
  • Experience translating business requirements into technical solutions and working with analysts, developers, data owners and stakeholders.
  • Experience supporting Power BI, analytics or AI use cases and helping a growing data function establish engineering standards.

Responsabilidades

  • Design, build, test and maintain reliable data pipelines that ingest data from ERP, operational and third-party systems.
  • Develop and maintain the Microsoft Fabric data platform using appropriate lakehouse/warehouse, pipeline and transformation capabilities.
  • Implement processes to ensure data is accurate, complete and timely.
  • Apply data governance, naming, metadata, retention and classification standards across the platform.
  • Translate business and reporting requirements into scalable technical designs and well-defined data products.
  • Provide trusted Gold-layer datasets and semantic-ready structures for BI, ML and AI use cases.
  • Identify and deliver improvements to engineering standards, automation, deployment practices and platform efficiency.
  • Evaluate new Microsoft Fabric capabilities and recommend adoption where they provide demonstrable business value.

Conocimientos

Strong SQL
Microsoft Fabric
Data Factory pipelines
Lakehouse / Warehouse
Notebooks
Power BI experience
Data governance
Cloud data platforms

Educación

Degree in data engineering / computer science / software engineering / mathematics

Herramientas

Microsoft Fabric
Data Factory pipelines
Lakehouse
OneLake
Notebooks
Power BI

Descripción del empleo

BRUSH Group in Loughborough is seeking a Data Engineer to design, build and operate robust data pipelines and platforms within the IT Data & AI team. You will connect source systems, apply the medallion architecture and deliver trusted data products using Microsoft Fabric, ensuring security, quality and governance.

You will collaborate with analysts and stakeholders to translate requirements into scalable data solutions, maintain data quality, and continuously improve deployment practices while

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