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For Companies At a Glance
- Tasks: Design and maintain data systems for investment insights and build data pipelines.
- Company: Join a forward-thinking team transforming private market data into actionable intelligence.
- Benefits: Hybrid work flexibility, professional growth opportunities, and a collaborative culture.
- Why this job: Make a real impact on investment strategies with hands-on engineering in data.
- Qualifications: 2+ years in data engineering, strong SQL, Python skills, and experience with APIs.
- Other info: Exciting chance to work with modern tools and cloud technologies.
The predicted salary is between 36000 - 60000 £ per year.
We’re looking for a detail-oriented and motivated Data Engineer to join on a 12-month fixed-term contract. You’ll help design and maintain the data systems that power investment insights — ensuring teams can access accurate, reliable, and well-structured data when they need it most.
This role sits within a team building a platform that transforms unstructured private market data into actionable intelligence. As a Data Engineer, you’ll play a key role in building pipelines, integrating data sources, and supporting the infrastructure that enables advanced analytics and machine learning.
You’ll work closely with engineers, analysts, and data scientists to ensure data is clean, consistent, and ready for use at scale. From database management to pipeline optimisation, you’ll be hands-on across the data lifecycle, helping turn complex datasets into meaningful insight.
What’s in it for you?
📊 Data That Drives Decisions – Work on systems that power real investment strategies and insights.
⚙ Hands-On Engineering – Build and optimise data pipelines, integrations, and infrastructure at scale.
📈 Professional Growth – Expand your skills in modern data engineering tools and cloud technologies.
🤝 Collaborative Culture – Work alongside engineers, analysts, and domain experts in a supportive environment.
🏢 Hybrid Flexibility – Balance focused remote work with in-person collaboration at our office.
What We’re Looking For:
- 2+ years of experience in data engineering or a similar role
- Strong SQL skills and familiarity with relational databases
- Proficiency in Python for data manipulation and pipeline development
- Experience working with APIs and integrating multiple data sources
- A systematic, detail-oriented approach to building reliable data systems
Nice to Have:
- Experience with cloud platforms (AWS, GCP, or Azure)
- Familiarity with workflow orchestration tools (e.g. Airflow, Prefect)
- Knowledge of data warehousing solutions and BI tools
- Exposure to financial datasets or document-heavy workflows
If you’re excited to work on meaningful data problems and help shape the way complex markets are understood — we’d love to hear from you.
Apply now and start your journey building the future of data-driven insight.
Data Engineer employer: Intellect Group
Contact Detail:
Intellect Group 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 your connections in the data engineering field and let them know you're on the lookout for opportunities. A friendly chat can lead to referrals or insider info about job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving SQL, Python, and data pipelines. 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 — it’s all about demonstrating your systematic approach!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love hearing from passionate candidates who are eager to join our collaborative culture.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data engineering, especially with SQL and Python. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the Data Engineer role and how your background makes you a perfect fit. We love seeing genuine enthusiasm for the work we do.
Showcase Your Technical Skills: Don’t forget to mention any experience with cloud platforms or workflow orchestration tools. If you’ve worked with APIs or financial datasets, let us know! We’re keen on candidates who can hit the ground running.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team!
How to prepare for a job interview at Intellect Group
✨Know Your Data Engineering Basics
Brush up on your SQL skills and be ready to discuss your experience with relational databases. Be prepared to explain how you've used Python for data manipulation and pipeline development in past projects.
✨Showcase Your Problem-Solving Skills
Think of specific examples where you’ve tackled complex data challenges. Whether it’s optimising a pipeline or integrating multiple data sources, having concrete stories will demonstrate your hands-on experience and systematic approach.
✨Familiarise Yourself with the Tools
If you have experience with cloud platforms like AWS, GCP, or Azure, make sure to highlight that. Also, if you’ve worked with workflow orchestration tools like Airflow or Prefect, be ready to discuss how they’ve helped you manage data workflows effectively.
✨Emphasise Collaboration
Since this role involves working closely with engineers, analysts, and data scientists, be prepared to talk about your collaborative experiences. Share how you’ve contributed to team projects and how you ensure data is clean and ready for use at scale.
