Data Engineer (Ref: 198123)

Our client manufactures fresh and slow-cooked meat products for the food industry, supplying a portfolio of brands from its established Irish operation. Founded in 1981 and headquartered in Clonee, the organisation combines large-scale food production with multi-site operational complexity, creating a substantial environment for data-led planning, performance management, and continuous improvement.

Operating within food and beverage manufacturing, this organisation relies on accurate information to coordinate production, understand performance, and support decisions across its brands and facilities. Its Preston-based data function will contribute to strengthening the systems and analytical foundations that connect operational activity with measurable business outcomes.

As Data Engineer, you will design, build, and enhance the data foundations supporting production planning analytics across a complex food manufacturing environment. The position carries substantial ownership, with responsibility for turning information from enterprise systems, legacy applications, and external services into dependable, accessible, and well-structured data assets.

Success will involve delivering robust pipelines, well-designed data models, and practical semantic layers that enable trusted analysis and clearer operational decisions. Working with considerable autonomy, you will help shape greenfield capability while ensuring that engineering standards, data quality, and maintainability remain appropriate for a growing analytics landscape.

Based in Preston, you will work across business and technical contexts, translating operational requirements into scalable engineering solutions. Your contribution will support production planning and may extend to data needs across wider UK operations, making this a visible role within the organisation’s continued development of its data capability.

• Design and deliver greenfield data engineering solutions for production planning analytics.
• Build, monitor, and improve reliable ETL processes and data pipelines.
• Integrate information from D365, legacy platforms, external APIs, and other operational sources.
• Develop logical and physical data models that support consistent reporting and analysis.
• Create and maintain semantic models that make complex operational data usable for business stakeholders.
• Apply strong SQL and Python practices to transform, validate, and manage data efficiently.
• Work independently from discovery through delivery, taking accountability for quality, documentation, and outcomes.
• Identify opportunities to extend data engineering support across Preston and other UK manufacturing locations.

• Professional experience delivering data engineering solutions in a commercial environment.
• Practical experience with Microsoft Fabric and its associated data engineering capabilities.
• Strong Python skills for data processing, automation, and pipeline development.
• Advanced SQL capability, including query optimisation and complex transformation logic.
• Hands-on experience designing and maintaining ETL workflows and production data pipelines.
• Proven ability to create data models that support reliable analytical and reporting use cases.
• Experience developing semantic models for business intelligence and self-service analysis.
• Confidence integrating data from enterprise platforms, legacy systems, APIs, and varied source formats.
• Ability to work autonomously, structure ambiguous requirements, and deliver maintainable solutions.
• Strong communication skills, with the judgement to explain technical decisions in an operational context.

• Meaningful ownership of a greenfield data engineering agenda with direct relevance to production planning.
• Exposure to Microsoft Fabric, D365, legacy system integration, external APIs, and multi-source data architecture.
• The opportunity to influence how operational data is modelled, governed, and used across a recognised food manufacturing environment.
• A role with visible impact on planning quality, reporting confidence, and decision-making across multiple brands and sites.
• Professional development through technically varied work spanning engineering, modelling, integration, and analytics enablement.
• Autonomy to shape solutions, establish sound engineering practices, and build capability rather than only maintain existing processes.
• Collaboration with stakeholders connected to manufacturing operations, creating a direct link between technical delivery and business performance.
• A competitive package aligned with the scope, autonomy, and specialist nature of the position.

The role is based in Preston, England, and is suited to a data engineer who combines technical depth with practical business judgement. Experience in manufacturing, food production, supply chain, or another operationally complex environment would be valuable, particularly where data must be assembled from diverse systems and converted into dependable planning insight.

Applicants should be comfortable taking a problem from an incomplete brief to a robust delivered solution. The successful individual will bring curiosity, discipline, and the confidence to establish new approaches while keeping the needs of production and planning teams at the centre of the work.