At a Glance
- Tasks: Own and evolve data pipelines, deploy ML systems, and maintain AWS-native data platform.
- Company: Stint is revolutionising hospitality with AI and a flexible student workforce.
- Benefits: Competitive salary, private medical insurance, office gym membership, and ownership shares.
- Other info: Enjoy a dog-friendly office with free snacks and regular team meals.
- Why this job: Join a fast-paced team and make a real impact in a growing start-up.
- Qualifications: Technical background in Computer Science or related field; strong data engineering skills.
The predicted salary is between 60000 - 80000 £ per year.
At Stint, we’re using AI tools to transform how hospitality businesses operate. We started by building the UK’s largest flexible workforce of hyper-local students available for short 2–3 hour shifts, working with brands like PizzaExpress, Pret a Manger, Gails, and many more. Now, we’re combining that workforce with an AI tool – creating a platform that no competitor can replicate. In just 10 months, our new AI software has surpassed £1m in ARR and we are on track to multiply that in the next 12 months. We are aggressively capturing the UK market, and international expansion is next - with plans to launch big in the US soon.
We’re looking for a Mid / Senior Data Engineer to become a key technical backbone of our data platform. You’ll take ownership of the infrastructure and pipelines that power our analytics and machine learning - ensuring data flows reliably from ingestion through to production models and real-time decisioning. This is a hands-on role focused on building, shipping, and maintaining robust data and ML systems. You’ll work closely with Data Scientists, Engineers, and Product teams to keep our platform running smoothly while continuously improving reliability, scalability, and performance. We are an office-first, collaborative team and this role is based in Camden 3-4 days a week.
What you will be doing:
- Own and evolve our data pipelines - designing, building, and maintaining ETL/ELT workflows that ensure high-quality, reliable data across the platform.
- Deploy and support production ML systems - from forecasting models to LLM-driven and agentic workflows - with proper monitoring, versioning, and CI/CD.
- Maintain and improve our AWS-native data platform (S3, Redshift, RDS, Athena, SageMaker, Lambda), driving operational best practices and platform reliability.
- Write and optimise complex SQL to support analytics, reporting, and data modelling for downstream teams and BI tooling.
- Build and maintain integrations with internal services and partner systems, ensuring clean and scalable data access.
- Act as a go-to technical partner for production data issues - diagnosing problems, improving resilience, and keeping systems running smoothly.
- Support and mentor junior team members through code reviews, pairing, and sharing best practices.
- Work closely with stakeholders across the business to translate data challenges into practical, scalable solutions.
This position might suit you, if:
- You’ve studied something technical - like Computer Science, Engineering, Mathematics, or a related field.
- You have strong data engineering fundamentals, including pipeline design, orchestration, testing, and monitoring.
- You’re confident writing production-quality Python and complex SQL across modern data platforms.
- You have hands-on experience deploying and running ML systems in production, including model serving and monitoring.
- You’re comfortable working across cloud infrastructure (ideally AWS) and understand platform and DevOps principles.
- You’re pragmatic and ownership-driven - happy to dive into problems, unblock others, and keep things running.
- You enjoy working in fast-moving environments where you can have real impact on how systems are built and scaled.
What we can offer you:
- Salary is competitive and open to discussion based on level.
- Private medical insurance.
- A social, friendly and welcoming team based in the heart of Camden.
- Office gym membership.
- Ownership shares in a well-funded, growing start-up.
- Dog friendly office!
- Free office fruit and snacks.
- Office dinner if working late.
- Regular office breakfasts and lunches.
Data Engineer employer: Stint
Contact Detail:
Stint Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Get out there and connect with people in the industry. Attend meetups, webinars, or even just grab a coffee with someone who works at Stint. Building relationships can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects. Whether it's a GitHub repo or a personal website, having tangible examples of your work can really impress hiring managers.
✨Tip Number 3
Prepare for the technical interview! Brush up on your SQL and Python skills, and be ready to discuss your experience with AWS and ML systems. Practising common data engineering problems can give you the edge you need.
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight how your skills align with what we’re doing at Stint, and let’s make some magic happen!
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with data pipelines, AWS, and any relevant projects that showcase your skills. We want to see how you can contribute to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data engineering and how your background aligns with our mission at Stint. Let us know why you're excited about the opportunity to work with AI in the hospitality sector.
Showcase Your Technical Skills: Don’t hold back on showcasing your technical skills! Include specific examples of your experience with Python, SQL, and ML systems. We’re looking for hands-on experience, so make it clear how you’ve applied your knowledge in real-world scenarios.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Stint
✨Know Your Data Engineering Fundamentals
Brush up on your data engineering basics, especially around pipeline design and orchestration. Be ready to discuss your experience with ETL/ELT workflows and how you've ensured data quality in past projects.
✨Showcase Your Technical Skills
Prepare to demonstrate your proficiency in Python and SQL. You might be asked to solve a problem or optimise a query during the interview, so practice writing production-quality code and think through your approach.
✨Familiarise Yourself with AWS Tools
Since the role involves maintaining an AWS-native data platform, make sure you understand services like S3, Redshift, and SageMaker. Be ready to discuss how you've used these tools in previous roles and any best practices you've implemented.
✨Emphasise Collaboration and Mentorship
This position values teamwork, so be prepared to talk about how you've collaborated with data scientists and engineers in the past. Highlight any mentoring experiences you have, as they’ll want to see your ability to support junior team members.