At a Glance
- Tasks: Design and maintain high-quality data pipelines for analytics and reporting.
- Company: Join JD Group, a leader in data engineering solutions.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: This is a 12-month maternity cover role with excellent career development prospects.
- Why this job: Make an impact by delivering reliable data solutions in a collaborative environment.
- Qualifications: Experience in SQL, Python, and building data pipelines is essential.
The predicted salary is between 50000 - 60000 £ per year.
We are seeking a delivery‑focused Data Engineer to design, build, and maintain high‑quality data engineering solutions within JD Group. Reporting to a Data Engineering Area Lead, you will play a key role in developing reliable, scalable data pipelines and curated datasets that support analytics, reporting, AI, and data product use cases.
You will work closely with other data engineers, analysts, BI developers, data scientists, and business stakeholders to ensure that data is accurate, accessible, and fit for purpose. This role is suited to an engineer who enjoys hands‑on development, takes ownership of their work, and is committed to engineering excellence and continuous improvement.
Responsibilities:- Design, build, test, and maintain data pipelines for ingestion, transformation, and curation of data from a variety of source systems.
- Deliver analytics‑ready datasets and data models that are reliable, well‑structured, and easy to consume.
- Work from clearly defined requirements and backlogs, contributing estimates, technical input, and delivery plans.
- Take ownership of assigned data engineering tasks and deliverables, ensuring work is completed to a high standard.
- Support incremental delivery and continuous improvement of data solutions.
- Write high‑quality, maintainable, and well‑tested code using SQL, Python, and approved data engineering frameworks.
- Apply data engineering standards across version control, CI/CD, testing, documentation, and observability.
- Ensure pipelines are performant, scalable, and cost‑efficient within cloud environments.
- Contribute to the development and reuse of common patterns, frameworks, and components.
- Actively manage and reduce technical debt within owned pipelines and datasets.
- Embed data quality checks, validation, and monitoring within pipelines.
- Ensure datasets meet agreed governance, security, and access control standards.
- Maintain clear documentation for pipelines, data models, and datasets.
- Participate in incident investigation, root‑cause analysis, and resolution of data issues.
- Support the ongoing operational health and reliability of data pipelines.
- Work closely with analysts, BI developers, and data scientists to understand data requirements and consumption needs.
- Collaborate with business stakeholders to clarify requirements and validate outputs.
- Communicate progress, risks, and technical considerations clearly to your Area Lead and wider team.
- Contribute constructively to team ceremonies, design discussions, and code reviews.
- Continuously develop technical skills and understanding of the business domain.
- Adopt and apply new tools, techniques, and patterns as agreed within the data engineering function.
- Share knowledge, best practices, and learnings with the wider data engineering community.
- Support and mentor junior data engineers where appropriate.
- High‑quality, timely delivery of assigned data engineering work.
- Reliable, well‑tested, and well‑documented data pipelines.
- Improved data quality and usability across owned datasets.
- Reduced incidents and faster resolution of data issues.
- Positive collaboration and feedback from peers and stakeholders.
- Consistent adherence to enterprise data engineering standards.
- Proven experience in a data engineering role.
- Strong hands‑on experience with SQL and Python.
- Experience building and maintaining data pipelines and transformations.
- Understanding of data modelling for analytics and reporting use cases.
- Experience working in cloud‑based data platforms, ideally GCP.
- Familiarity with orchestration tools, batch processing, and structured data pipelines.
- Experience with version control, CI/CD, and basic testing practices.
- Ability to work independently on well‑scoped problems and deliver incrementally.
- Strong attention to detail and commitment to data quality.
Data Engineer (Maternity Cover 12 month FTC) in Bury employer: JD Sports
At JD Group, we pride ourselves on being an excellent employer that fosters a collaborative and innovative work culture. As a Data Engineer, you will have the opportunity to work with cutting-edge technologies in a supportive environment that encourages continuous learning and professional growth. Our commitment to engineering excellence and data quality ensures that you will be part of a team that values your contributions and invests in your development, making this a rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer (Maternity Cover 12 month FTC) in Bury
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like JD Sports before they're even advertised!
✨Show Off Your Skills With Projects
Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
✨Check Out Specialist Job Boards
For temp roles, hit up job boards dedicated to tech and data science, like Stack Overflow Jobs or DataJobs. These platforms often feature openings that you won’t find on general job sites, including contracts with companies like JD Sports.
✨Leverage University Resources
If you're currently at uni or recently graduated, tap into your school's career services. They often have connections with companies looking for temporary data science interns or contract workers, and they might even host job fairs with employers like JD Sports.
We think you need these skills to ace Data Engineer (Maternity Cover 12 month FTC) in Bury
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at JD Sports, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to JD Sports, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab JD Sports’s attention and show the tangible impact of your work.
How to prepare for a job interview at JD Sports
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at JD Sports.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at JD Sports.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at JD Sports.
