Data Engineer

About Classic Football Shirts

Classic Football Shirts started in 2006 when university friends Matt Dale and Doug Bierton set out to track down rare football shirts. From those early days in a bedroom full of rails, the company has grown into a thriving business with a talented team, a busy warehouse, and stores in Manchester, London, and the US.

Our passion for football and the stories behind every shirt drives everything we do. At Classic Football Shirts, we work together, stay grounded, and always put our fans at the heart of the business. We share the passion, win together, stay fan-focused, be agile, and stay grounded — values that guide how we operate every day.

To find out more about our story so far please follow this link: https://www.classicfootballshirts.co.uk/about-us

We welcome all suitably qualified applicants and are committed to creating an inclusive environment for all our employees. We have a great work ethic and a friendly group of diverse employees who enjoy working here to help carry out our mission.

The Role:

As a Data Engineer, you’ll be an integral part of our team, contributing to the development and performance of our data infrastructure and capabilities. This role involves close collaboration with the development team, business analysts, and key internal stakeholders to design, build, and improve data systems through solution design, data pipelines & AI.

You will play a key role in designing and delivering data solutions that meet business requirements, ensuring that systems are efficient, scalable, and aligned with organisational goals. This includes taking ownership of the full data lifecycle, from ingestion and modelling to integration and delivery while maintaining high standards of quality and documentation.

This role is ideal for someone with a solid grounding in data concepts and a genuine interest in applying and developing their technical and solution design skills in a real-world business environment. While you’re not expected to know everything on day one, you should have a problem-solving mindset, a willingness to learn, and some practical experience working with data. Your work will contribute to building solutions that help drive better operational performance and business decisions to support day-to-day operations.

Location: Manchester, Hybrid

Hours: The role is a full-time position

Key Responsibilities:

• Design, document, and deliver end-to-end data solutions, ensuring alignment with architectural best practices, scalability, and business needs.
• Work closely with business and technical stakeholders to gather and interpret requirements, translating them into clear, actionable technical designs.
• Design, develop, and maintain robust data pipelines (ETL/ELT) to ensure reliable, automated data flow between internal and external systems.
• Integrate and manage data from a variety of sources including relational databases, APIs, and cloud platforms.
• Model, structure, and transform data to maintain high quality, consistency, and efficiency across analytical and operational systems.
• Develop, test, and deploy automated data workflows and orchestration using tools such as Airflow, DBT, or similar frameworks.
• Build, maintain, and enhance data models and semantic layers to support BI, analytics, and AI initiatives.
• Collaborate with analysts and business teams to develop and evolve dashboards and reports, enabling clear, actionable insight.
• Contribute to the solution design and architecture of new data products and integrations, ensuring technical soundness and maintainability.
• Monitor and optimise performance of data pipelines and warehouse queries, implementing improvements where needed.
• Champion data quality and governance, implementing validation and monitoring to ensure accuracy and reliability.
• Document all data systems, models, and workflows to ensure transparency, reusability, and long-term maintainability.
• Collaborate with other departments to evaluate new tools and technologies, contributing to the evolution of the company’s data strategy and capabilities.
• Get involved with AI and automation initiatives, identifying where modern data solutions can drive efficiency and innovation.
• Provide occasional out-of-hours support where required to ensure continuity of key data operations.

About You/Qualifications:

• Strong understanding of data engineering principles, including data pipelines, ETL/ELT processes, data warehousing, and solution design.
• Proven ability to design, document, and deliver scalable data solutions from requirements gathering through to deployment.
• Ability to lead or contribute to technical design discussions, ensuring solutions are robust, maintainable, and aligned with business needs.
• Proficiency in Python for data transformation, automation, and integration tasks, and SQL for building and optimising complex queries.
• Hands-on experience with cloud data platforms, ideally Google Cloud Platform (BigQuery, Cloud Storage, Cloud Functions) or equivalents such as AWS Redshift or Azure Synapse.
• Practical experience using modern data tooling such as DBT, Airflow, or Prefect for orchestration, transformation, and workflow automation.
• Experience designing and maintaining data models and schemas to support reporting, analytics, and machine learning workloads.
• Familiarity with data integration from APIs and third-party systems, and strong awareness of data quality, validation, and governance best practices.
• Understanding of version control (Git) and continuous integration / deployment (CI/CD) workflows.
• Awareness of AI and machine learning workflows, including data preparation for model training and production use (e.g. Vertex AI, Databricks, or similar)
• Strong problem-solving and analytical skills, with the ability to identify and resolve issues independently.
• Clear communication skills and the ability to collaborate effectively with both technical and non-technical teams.
• E-commerce or retail data experience is beneficial but not essential.
• Continuous improvement mindset, with enthusiasm for automation, scalability, and adopting new technologies to improve data systems.

Application:

• Application method: please email CV and Cover Letter to
• Please note: We are not engaging with recruitment agencies for this role, so we kindly ask that agencies do not contact us regarding this vacancy.