Biffa

Data Engineering

Hybrid Role - 2 days office based

Mon-Fri 37.5 hours per week

At Biffa, we're transforming how data is used across our business, moving beyond traditional reporting towards advanced analytics, automation, and AI-driven decision making. As a Data Engineer, you'll play a key role in designing and building the data platforms, pipelines and architecture that underpin critical business insights across operations, customer services, finance and commercial functions.

Working with Microsoft Fabric, Azure Data Lake, Azure SQL and modern cloud technologies, you'll help create reliable, scalable and high-quality data solutions that enable better decisions, improve efficiency and unlock business value. If you're passionate about data engineering, enjoy solving complex challenges, and want to make a real impact in a business that's investing heavily in its data future, we'd love to hear from you.

Your core responsibilities

• Design, build and maintain scalable data pipelines and data integration solutions.
• Develop and support data ingestion, transformation and storage processes.
• Work with business, analytics and application teams to deliver trusted data products.
• Ensure data is reliable, secure, performant and available for reporting and analytics.
• Support data quality, monitoring, troubleshooting and issue resolution.
• Contribute to data architecture, standards and engineering best practices.
• Produce technical documentation and provide knowledge transfer to internal teams.

Our essential requirements

• 5+ years' experience in data engineering or related data platform roles.
• Strong understanding of data warehousing, lakehouse and analytical data architectures.
• Expertise in SQL, Python and data modelling techniques
• Experience with Azure Data Factory, Microsoft Fabric and/or Azure Data Services.
• Proficiency in data transformation and orchestration technologies.
• Experience working with structured, semi-structured and large-volume datasets.
• Knowledge of data governance, security and data quality practices.
• Strong troubleshooting, optimisation and performance tuning skills.