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For Companies At a Glance
- 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: Flexible working hours, hybrid role, and a full home-working setup provided.
- Why this job: Make a real impact by shaping data products and collaborating with diverse teams.
- Qualifications: Strong SQL skills, experience with Python, and a keen eye for detail.
- Other info: Great career growth opportunities and a chance to work with cutting-edge AI tools.
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. Day to day, you will:
- 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 in Manchester employer: Circle Group
Contact Detail:
Circle Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer in Manchester
✨Tip Number 1
Network like a pro! Reach out to folks in the data engineering field on LinkedIn or at local meetups. We can’t stress enough how valuable personal connections can be in landing that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your SQL and Python projects. We love seeing real-world applications of your work, so make sure it’s easy to access and highlights your best stuff.
✨Tip Number 3
Prepare for those interviews! Brush up on common data engineering questions and be ready to discuss your approach to data quality and schema design. We want to see your thought process, so practice articulating it clearly.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for passionate candidates who are eager to dive into the data world.
We think you need these skills to ace Data Engineer in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Engineer role. Highlight your SQL and Python expertise, and don’t forget to mention any hands-on data projects you've worked on!
Showcase Your Attention to Detail: Since this role is all about data quality and consistency, include examples in your application that demonstrate your meticulous nature. Whether it’s a project where you improved data reliability or a time you caught an error, we want to see it!
Communicate Clearly: Your written application should be clear and concise. Use straightforward language to explain your experience and how it relates to the job. Remember, we value collaboration, so showing you can communicate well is key!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be one step closer to joining our awesome Data Products team!
How to prepare for a job interview at Circle Group
✨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. This will show that you’re not just familiar with the tools but can also apply them effectively.
✨Understand the Role's Focus
This position is all about transforming messy data into reliable datasets. Prepare examples of how you've tackled similar challenges in the past. Highlight your attention to detail and how you ensure data quality, as this is crucial for the role.
✨Collaborate and Communicate
Since the role involves working closely with various teams, think of instances where you've successfully collaborated with engineers or product managers. Be ready to discuss how you communicate complex data concepts to non-technical stakeholders, as this will demonstrate your ability to bridge gaps between teams.
✨Show Your Passion for Data Quality
Express your enthusiasm for data quality and governance during the interview. Discuss any experiences you have with validation rules or quality checks, and be prepared to share your thoughts on best practices for maintaining data integrity. This will resonate well with the interviewers looking for someone who truly cares about data.
