Data Engineer (Enterprise Data & Intelligence)

About the role

As a Data Engineer on the Enterprise Data & Intelligence team, you will design, build and maintain the data pipelines and models that form Fourth’s single source of truth. You will translate business requirements into reliable, well‑tested data solutions on an Azure‑based cloud platform and collaborate with analytics engineers and business stakeholders across FP&A, Commercial, Product and AI teams.

Key responsibilities

• Build, maintain and optimise scalable ETL/ELT pipelines (batch and near‑real‑time) using Azure Data Lake, Microsoft Fabric and Azure Data Factory.
• Develop and refine data models to support BI reporting, analytics and machine‑learning use cases, writing efficient T‑SQL and PySpark code.
• Implement automated testing, data validation and monitoring to ensure pipeline reliability and contribute to data governance practices.
• Partner with analytics engineers and business stakeholders to scope, prioritise and deliver production‑ready data solutions.
• Contribute to platform evolution, tooling, standards and documentation while leveraging AI productivity tools for code generation, testing and documentation.

Required profile

• 3+ years of experience in data engineering or a closely related role.
• Bachelor’s degree in Computer Science, Data Engineering or a related field.
• Strong analytical mindset, proactive communication and ability to work in an agile, fast‑paced environment.

Required skills

• T‑SQL
• PySpark / Python
• Azure Storage Explorer
• SQL Server Management Studio (SSMS)
• Azure Data Factory
• Microsoft Fabric
• CI/CD practices (Git, automated testing)
• AI productivity tools (ChatGPT, Claude, Copilot, Cursor)
• PowerShell (preferred)
• Apache Kafka (preferred)
• KQL (preferred)
• Power BI (preferred)

What we offer

• 25+ days of annual leave plus birthday and charity days.
• Flexible start/end times and hybrid working mode.
• Team‑centric atmosphere with health‑insurance supplement.
• New‑parents bonus scheme.