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- Tasks: Own the analytics engineering process and design scalable data models.
- Company: Fast-growing FinTech company with a dynamic data team.
- Benefits: Remote work, competitive pay, and a chance to shape innovative products.
- Other info: Great opportunity for career growth and autonomy in your role.
- Why this job: Make a real impact in a fast-paced environment while driving data solutions.
- Qualifications: Experience in analytics engineering and strong dbt skills required.
The predicted salary is between 60000 - 80000 £ per year.
We’re partnered with one of the fastest-growing FinTech companies in Europe, currently expanding their data team following several new product launches. As a result of this rapid growth, there’s now a significant backlog of data requests across the business. They’re looking for Senior to Lead level Analytics Engineers who can step in quickly, take ownership of the analytics engineering lifecycle, and help drive delivery. This is a great opportunity to work in a fast-paced product environment, helping shape scalable data models and analytics foundations for new products.
What you’ll be doing:
- Owning the end-to-end Analytics Engineering process
- Working directly with stakeholders to gather requirements and translate business needs into data solutions
- Designing scalable data models and analytics architecture
- Building and maintaining clean, reliable transformation layers using dbt
- Supporting experimentation and incrementality analysis
- Delivering high-quality data models that enable product and business teams to move faster
What they’re looking for:
- Senior / Lead Analytics Engineering experience
- Proven experience owning projects end-to-end – from requirement gathering through to model design and implementation
- Strong dbt experience (essential)
- Experience designing scalable data models and analytics architecture
- Comfortable working directly with product and business stakeholders
- Experience working in fast-paced product environments
- Exposure to experimentation frameworks / incrementality analysis
If you’re an experienced Analytics Engineer who enjoys ownership, autonomy, and building scalable data foundations in product-led companies, this could be a great fit.
Senior Data Engineer in Portsmouth employer: Cognify Search
Contact Detail:
Cognify Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer in Portsmouth
✨Tip Number 1
Network like a pro! Reach out to your connections in the FinTech space and let them know you're on the lookout for opportunities. A personal recommendation can go a long way in landing that Senior Data Engineer role.
✨Tip Number 2
Showcase your skills! Create a portfolio or GitHub repository with examples of your work, especially focusing on dbt projects and scalable data models. This will give potential employers a clear view of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your analytics engineering lifecycle knowledge. Be ready to discuss how you've owned projects from start to finish and how you’ve collaborated with stakeholders to deliver high-quality data solutions.
✨Tip Number 4
Don’t forget to apply through our website! We’re always looking for talented individuals like you to join our team. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Senior Data Engineer in Portsmouth
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your Senior/Lead Analytics Engineering experience and any relevant projects you've owned from start to finish.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of how you've designed scalable data models or worked with stakeholders to gather requirements.
Showcase Your dbt Skills: Since strong dbt experience is essential, be sure to mention any projects where you've used dbt to build and maintain transformation layers. We want to see how you’ve made data clean and reliable!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates during the process.
How to prepare for a job interview at Cognify Search
✨Know Your Data Inside Out
Before the interview, make sure you’re well-versed in the data engineering lifecycle. Brush up on your experience with dbt and be ready to discuss specific projects where you’ve designed scalable data models. This will show that you can hit the ground running.
✨Speak Their Language
Familiarise yourself with the company’s products and how they use data. Be prepared to translate business needs into data solutions during the interview. This demonstrates your understanding of their environment and how you can contribute effectively.
✨Showcase Your Ownership Skills
Prepare examples of past projects where you took ownership from start to finish. Highlight how you gathered requirements, designed models, and implemented solutions. This will illustrate your capability to manage the analytics engineering process independently.
✨Engage with Stakeholders
Since the role involves working directly with product and business stakeholders, think of ways to demonstrate your communication skills. Share experiences where you successfully collaborated with non-technical teams to deliver data solutions that met their needs.