Data Engineer

Sanderson Recruitment Plc
London, UK
16 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
£90,000.0
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Continuous Integration Data Governance Data Infrastructure Data Integrity Data Systems MongoDB Power BI SQL Databases Delivery Pipeline Apache Spark Git
+4 more
Microsoft Fabric Data Analytics Graphql Data Pipelines

Job description

My client is looking for a Data Engineer with strong Microsoft Fabric expertise to own and develop the data platform, pipelines and reporting that support the business. You’ll work closely with Engineering, Product and commercial teams to turn business requirements into scalable, secure and trusted data solutions., * Microsoft Fabric: Own and optimise the Fabric environment across OneLake, Lakehouse, Warehouse, Data Factory, Dataflows Gen2, Spark notebooks, semantic models and DirectLake.

  • Data Engineering & Analytics: Build and orchestrate robust data pipelines from MongoDB, APIs and third-party sources, using SQL, Spark and modern data modelling to create performant, analytics-ready data-sets and Power BI reporting.
  • Data Quality & Governance: Take ownership of data integrity, profiling and reconciliation, implementing quality checks and governance frameworks to identify issues early and maintain a well-structured, compliant and cost-efficient Fabric environment.
  • Business Partnership: Work with Engineering, Product and commercial stakeholders to understand data requirements, translate business questions into actionable specifications and deliver clear, trustworthy analysis and visual insight.
  • Modern Data Practices: Apply Git, CI/CD and Fabric deployment pipelines, alongside strong security, RLS, GDPR/PII and metadata practices, while evaluating emerging technologies to continually improve the wider data capability.

Requirements

Key skills: Microsoft Fabric, OneLake, Lakehouse, Warehouse, Data Factory, Dataflows Gen2, Spark, SQL, Power BI, DAX, DirectLake, MongoDB, REST/GraphQL APIs, Git/CI/CD, data modelling, data governance, data quality and GDPR/PII.

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