At a Glance
- Tasks: Evolve and scale a cloud-based analytics platform in the fintech space.
- Company: Established payments technology business with a modern, engineering-led culture.
- Benefits: £60,000 salary, remote work, and opportunities for professional growth.
- Other info: Autonomous environment with a focus on innovation and collaboration.
- Why this job: Join a dynamic team using AI to shape the future of payments analytics.
- Qualifications: Strong SQL skills and experience with data warehouses required.
The predicted salary is between 60000 - 60000 £ per year.
Pulse are currently partnering with an established payments technology business looking to hire an Analytics Engineer to help evolve and scale a modern cloud-based analytics platform.
Operating within the payments and fintech space, the business processes large volumes of transaction data across card payments, pay-by-bank, payouts, recurring payments, and merchant services. This is a genuinely interesting role sitting between analytics engineering, commercial insight, and modern AI-enabled ways of working.
You’ll work closely with Product, Commercial, Finance, and Engineering teams to help shape how the business understands:
- Merchant and transaction performance
- Product adoption and conversion
- Revenue, margin, and commercial metrics
- Customer and payment behaviour
- Pipeline-to-activation performance
- Operational and financial reporting
The environment is modern, engineering-led, and highly autonomous. The team already uses AI heavily across analytics and engineering workflows and is actively exploring how AI tooling can improve modelling, documentation, investigation, and delivery practices.
Tech environment includes:
- SQL
- BigQuery
- DBT
- Semantic Layer / dimensional modelling
- Looker Studio
- HubSpot and commercial data integrations
- AI tooling embedded into engineering and analytics workflows
What they’re looking for:
- Strong SQL capability
- Experience working with data warehouses and analytics workflows
- Someone commercially minded who can work directly with stakeholders across the business
- A self-starter comfortable operating with high autonomy and ownership
- Interest in modern analytics engineering and AI-assisted ways of working
- Someone capable of critically evaluating AI outputs rather than relying on them blindly
This could suit:
- An Analytics Engineer looking for broader ownership
- A strong Analyst wanting to move deeper into engineering and modelling
- Someone already operating in a hybrid analytics / engineering environment
£60,000 base salary. Remote-first with occasional meetups in the East Midlands / London.
Data Engineer employer: Pulse Recruit
Join a forward-thinking FinTech payments company that champions innovation and autonomy, offering a dynamic work culture where your contributions directly impact the evolution of a cutting-edge analytics platform. With a strong emphasis on employee growth, you will have the opportunity to collaborate with diverse teams and leverage modern AI tools, all while enjoying the flexibility of remote work with occasional meetups in the vibrant East Midlands. This role not only promises a competitive salary but also a chance to be at the forefront of analytics engineering in a rapidly evolving industry.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the fintech and analytics space on LinkedIn. Join relevant groups, attend virtual meetups, and don’t be shy about sliding into DMs. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your SQL projects or any analytics work you've done. This is your chance to demonstrate your capabilities beyond just a CV. Share it during interviews or even in your LinkedIn profile!
✨Tip Number 3
Prepare for those interviews! Research the company’s tech stack and think about how your experience aligns with their needs. Be ready to discuss how you can contribute to their AI-driven analytics workflows and improve their data processes.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be perfect for you. Plus, applying directly shows your enthusiasm and makes it easier for us to connect with you!
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Show Off Your SQL Skills:Make sure to highlight your SQL capabilities in your application. We want to see how you can manipulate and analyse data, so don’t hold back on sharing specific examples of your work with SQL and data warehouses.
Be Commercially Minded:Since this role involves working closely with various teams, it’s important to demonstrate your understanding of commercial metrics. We love seeing candidates who can connect the dots between data and business outcomes, so share any relevant experiences!
Emphasise Your Autonomy:We value self-starters who thrive in an autonomous environment. In your application, let us know about times when you took ownership of a project or task and how you navigated challenges independently.
Express Your Interest in AI:As we’re heavily into AI-assisted workflows, show us your enthusiasm for modern analytics engineering. Mention any experience you have with AI tools or how you’ve critically evaluated AI outputs in your previous roles.
How to prepare for a job interview at Pulse Recruit
✨Know Your SQL Inside Out
As a Data Engineer, strong SQL skills are crucial. Brush up on your SQL queries and be ready to discuss how you've used them in past projects. Prepare to solve some SQL problems during the interview to showcase your expertise.
✨Understand the Business Context
Familiarise yourself with the payments and fintech landscape. Understand how transaction data impacts merchant performance and customer behaviour. This will help you engage meaningfully with stakeholders and demonstrate your commercial mindset.
✨Showcase Your AI Knowledge
Since the role involves AI tooling, be prepared to discuss your experience with AI in analytics. Share examples of how you've critically evaluated AI outputs and improved processes using AI tools. This will highlight your modern approach to analytics engineering.
✨Emphasise Autonomy and Ownership
The company values self-starters who can work independently. Be ready to share instances where you've taken ownership of projects or initiatives. Highlight your ability to operate autonomously while still collaborating effectively with teams.
