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- Tasks: Transform messy data into clean, reliable datasets for teams and clients.
- Company: Join a forward-thinking tech company with a focus on data innovation.
- Benefits: Enjoy flexible working hours, hybrid setup, and a full home-working kit.
- Why this job: Make a real impact by shaping data products and improving data quality.
- Qualifications: Strong SQL skills and experience with Python or similar data-friendly languages.
- Other info: Collaborative environment with opportunities for growth and learning.
The predicted salary is between 28800 - 48000 £ per year.
Not every data role is about dashboards or ad-hoc analysis. This one is for someone who enjoys getting close to the data itself, taking messy, real-world raw data and turning it into clean, reliable datasets that other teams and clients can actually trust and use. It's a hands-on role sitting at the intersection of data modelling, quality and product thinking, with plenty of ownership and room to influence how data products are designed and evolved.
What you'll be working on:
- You'll be part of a Data Products team responsible for shaping behavioural data into well defined, client ready datasets.
- Design and evolve data schemas and fields, turning product requirements into clear, well modelled datasets.
- Build and maintain data feeds using SQL, Python and internal (AI-assisted) tooling.
- Apply business logic, validation rules and quality checks across large datasets.
- Investigate data issues and improve reliability, consistency and trust in the outputs.
- Work closely with Product, Data Engineering, Apps and ML teams to deliver new features and improvements.
- Keep documentation clear, current and genuinely useful.
This is a role for someone who cares about how data is structured, named and validated, not just whether a query runs.
Who this role suits:
- This role is a good fit if you enjoy working hands on with data rather than sitting at arm's length from it.
- Like figuring out how real-world digital behaviour should be represented cleanly.
- Care about data quality, edge cases and consistency.
- Are comfortable collaborating with engineers, product managers and non-technical stakeholders.
- Are open to using AI tools to speed up understanding and reduce repetitive work.
You'll likely bring:
- Strong SQL skills and experience working with large datasets.
- Experience with at least one data-friendly language (such as Python).
- A high level of attention to detail.
- Clear communication skills and a collaborative mindset.
Nice to have (but not essential):
- Experience with event-level or behavioural data (web, apps, ads, etc.).
- Awareness of privacy and governance considerations.
- Familiarity with AWS-based data stacks (S3, Spark/EMR, Athena, Airflow, notebooks).
How you'll work:
- Hybrid role, Manchester-based 2 days per week in the office, the rest flexible.
- Flexible start and finish times.
- Full home-working setup provided.
Data Engineer / Data Product Engineer in Manchester employer: Circle Recruitment
Contact Detail:
Circle Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer / Data Product Engineer in Manchester
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with data professionals on LinkedIn. 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, especially those involving SQL and Python. 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 scenarios. Practice explaining your thought process when tackling data problems, as this will demonstrate your hands-on approach and problem-solving skills.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Engineer / Data Product Engineer in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Data Engineer. Highlight your SQL and Python skills, and any experience with large datasets. We want to see how your background aligns with our needs!
Showcase Your Projects: If you've worked on any data projects, whether in a professional or personal capacity, include them! We love seeing how you've tackled messy data and turned it into something reliable. It shows us your hands-on experience.
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language and avoid jargon unless it's relevant. We appreciate a well-structured application that gets to the point without fluff.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Don’t miss out!
How to prepare for a job interview at Circle Recruitment
✨Know Your Data Tools
Make sure you brush up on your SQL and Python skills before the interview. Be ready to discuss how you've used these tools in past projects, especially when it comes to cleaning and structuring data. Showing that you can handle messy datasets will definitely impress!
✨Understand the Role's Impact
This role is all about transforming raw data into reliable datasets. Think about how your work can influence product design and decision-making. Be prepared to share examples of how you've improved data quality or reliability in previous roles.
✨Collaboration is Key
Since you'll be working closely with various teams, highlight your collaborative experiences. Share specific instances where you successfully communicated complex data concepts to non-technical stakeholders. This shows you can bridge the gap between data and product thinking.
✨Stay Current with AI Tools
Familiarise yourself with any AI-assisted tools mentioned in the job description. If you've used similar tools before, talk about how they helped streamline your work. Showing that you're open to leveraging technology will demonstrate your adaptability and forward-thinking approach.