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- Tasks: Join our Data Team to enhance data integration and support business users with seamless data experiences.
- Company: Wheely, a forward-thinking platform prioritising user privacy and exceptional service.
- Benefits: Flexible working hours, stock options, and a fantastic range of perks.
- Why this job: Make an impact in a dynamic environment while working with cutting-edge data technologies.
- Qualifications: 3+ years in Data Engineering, strong SQL and Python skills, and teamwork experience.
- Other info: Office-based role in West London with excellent career growth opportunities.
The predicted salary is between 36000 - 60000 £ per year.
Wheely is not a traditional ride-hailing company. We are building a platform with user privacy at its core while successfully scaling a five-star service to millions of rides across multiple cities. 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
Wheely expects the very best from our people, both on the road and in the office. In return, employees enjoy flexible working hours, stock options and an exceptional range of perks and benefits. Office-based role located in West London. Competitive salary.
Data Engineer employer: Wheely
Contact Detail:
Wheely 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. Ask them about their experiences and any tips they might have for landing the Data Engineer role.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your data projects, especially those involving Snowflake, Kafka, or Airflow. This will give you an edge and demonstrate your hands-on experience.
✨Tip Number 3
Get ready for the interview! Brush up on your SQL and Python skills, and be prepared to discuss how you've tackled performance bottlenecks in past projects. We want to see your problem-solving skills in action!
✨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 align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can contribute to our mission at Wheely. Keep it concise but impactful – we love a good story!
Showcase Your Projects: If you've worked on any cool data projects, don’t forget to mention them! Whether it's a personal project or something from your previous job, we want to see your hands-on experience and creativity in action.
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’re considered for the role. Plus, it’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at Wheely
✨Know Your Tech Stack
Make sure you’re familiar with the technologies mentioned in the job description, like Snowflake, Kafka, and dbt. Brush up on your SQL and Python skills, and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled data quality issues or performance bottlenecks in previous roles. Wheely values a proactive approach, so demonstrate your ability to identify and resolve challenges effectively.
✨Understand the Business Context
Research Wheely’s mission and how they prioritise user privacy. Be ready to discuss how your role as a Data Engineer can enhance the user experience and support business goals, showing that you’re not just about the tech but also about the impact.
✨Emphasise Team Collaboration
Wheely is looking for someone who can work well within a team. Prepare to talk about your experience with GitOps, code reviews, and how you’ve contributed to a collaborative environment in past positions.
