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For Companies At a Glance
- Tasks: Design and deliver innovative data solutions while collaborating with a passionate team.
- Company: Join Classic Football Shirts, a vibrant company driven by a love for football.
- Benefits: Enjoy a hybrid work environment, competitive salary, and opportunities for professional growth.
- Other info: Be part of a friendly, diverse team committed to excellence and innovation.
- Why this job: Make an impact in the world of football by enhancing our data capabilities.
- Qualifications: Experience in data engineering principles and a passion for problem-solving.
The predicted salary is between 36000 - 60000 £ per year.
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. 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 recruitment@classicfootballshirts.co.uk. 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.
Data Engineer employer: CLASSIC FOOTBALL SHIRTS LIMITED
Contact Detail:
CLASSIC FOOTBALL SHIRTS LIMITED Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, whether it's a cool data pipeline you built or an insightful dashboard. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and practical tasks. Practice coding challenges and be ready to discuss your past experiences and how they relate to the role at Classic Football Shirts.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of our team and culture.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight relevant experience and skills that match the job description, especially around data pipelines, ETL processes, and any tools like Python or SQL you've used.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about data engineering and how your background aligns with our mission at Classic Football Shirts. Keep it engaging and personal!
Showcase Your Problem-Solving Skills: We love a good problem-solver! In your application, share examples of challenges you've faced in previous roles and how you tackled them. This will show us your analytical mindset and ability to think on your feet.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the team!
How to prepare for a job interview at CLASSIC FOOTBALL SHIRTS LIMITED
✨Know Your Data Engineering Basics
Before the interview, brush up on your understanding of data pipelines, ETL/ELT processes, and data warehousing. Be ready to discuss how you've applied these principles in past projects, as this will show your practical experience and problem-solving mindset.
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in Python and SQL during the interview. Prepare examples of how you've used these languages for data transformation and automation tasks. This will demonstrate your technical capabilities and readiness to tackle the role's challenges.
✨Prepare for Collaboration Questions
Since the role involves working closely with various teams, be prepared to discuss your experience collaborating with both technical and non-technical stakeholders. Think of specific examples where you gathered requirements or translated technical designs into actionable insights.
✨Emphasise Your Continuous Improvement Mindset
Classic Football Shirts values innovation and efficiency, so share your enthusiasm for adopting new technologies and improving data systems. Discuss any experiences where you've implemented automation or optimised data workflows, as this aligns with their mission and values.