Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join our Data Team to enhance data pipelines and support business users with seamless data experiences.
- Company: Wheely, a high-end ride-hailing service redefining premium transportation.
- Benefits: Flexible hours, stock options, competitive salary, and top-notch perks.
- Why this job: Be part of a fast-growing scale-up and make an impact in the tech-driven transport industry.
- Qualifications: 3+ years in Data Engineering, fluent in SQL and Python, and strong teamwork skills.
- Other info: Office-based in West London with opportunities for remote work.
The predicted salary is between 36000 - 60000 £ per year.
Wheely is a high-end ride-hailing service redefining premium transportation across major cities in Europe and the Middle East. We combine technology with the art of five-star chauffeuring to deliver a consistently exceptional experience. As a profitable, fast-growing scale-up with $43M raised, we are expanding rapidly across EMEA and the US. We are looking for a Data Engineer to strengthen our Data Team at Wheely, proactively seeking and providing Business Users and Data Scientists with best-in-class and seamless data experience.
Responsibilities:
- Enhance Data team with architectural best practices and low-level optimizations
- Support on evolving data integration pipelines (Debezium, Kafka, dlt), data modelling (dbt), database engines (Snowflake), ML Ops (Airflow, MLflow), BI reporting (Metabase, Observable, Text-2-SQL), reverse ETL syncs (Census)
- Cover up business units with feature requests / bugfixes / data quality issues
- Enforce code quality, automated testing and code style
Requirements:
- 3+ years of experience in Data Infrastructure Engineer / Data Engineer / MLOps Engineer roles
- Have work experience or troubleshooting experience in the following areas:
- Analytical Databases: configuration, troubleshooting (Snowflake, Redshift, BigQuery)
- Data Pipelines: deployment, configuration, monitoring (Kafka, Airflow or similar)
- Data Modeling: DRY and structured approach, applying performance tuning techniques
- Containerizing applications and code: Docker, k8s
What we Offer:
- Flexible working hours
- Stock options
- Exceptional range of perks and benefits
- Office-based role located in West London
- Competitive salary & equity package
- Life and critical illness insurance
- Monthly credit for Wheely journeys
- Cycle to work scheme
- Top-notch equipment
- Relocation allowance (dependent on role level)
Wheely has an in-person culture but allows flexible working hours and work from home when needed.
Data Engineer employer: Wheely Ltd.
Contact Detail:
Wheely Ltd. 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 current employees at Wheely on LinkedIn or other platforms. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a mini-project or a portfolio that highlights your experience with data pipelines, SQL, and Python. This hands-on demonstration can really set you apart during interviews.
✨Tip Number 3
Be ready to discuss real-world problems! Think of examples where you've tackled data quality issues or optimised performance. Wheely loves candidates who can think critically and solve problems on the spot.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the Wheely team.
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 at Wheely. Highlight your experience with data pipelines, SQL, and any relevant technologies like Snowflake or Kafka. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're excited about joining Wheely and how you can contribute to our Data Team. Be genuine and let your personality come through – we love that!
Showcase Your Projects: If you've worked on any cool data projects, make sure to mention them! Whether it's a personal project or something from a previous job, showcasing your hands-on experience can really set you apart. We’re keen to see what you’ve done!
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 at Wheely!
How to prepare for a job interview at Wheely Ltd.
✨Know Your Tech Stack
Familiarise yourself with the specific technologies mentioned in the job description, like Snowflake, Kafka, and dbt. Be ready to discuss your experience with these tools and how you've used them to solve real-world problems.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled data quality issues or optimised data pipelines in the past. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your impact.
✨Understand the Business Context
Research Wheely's business model and how data plays a role in enhancing their premium ride-hailing service. This will help you connect your technical skills to their business needs during the interview.
✨Ask Insightful Questions
Prepare thoughtful questions about the Data Team's current projects or challenges they face. This shows your genuine interest in the role and helps you assess if Wheely is the right fit for you.
