Data Engineer

Wheely; City Of London; On-site; GBP 60,000 - 80,000; Full time

Job summary

A dynamic ride-hailing platform is seeking a Data Engineer to join their Data Team. The successful candidate will focus on enhancing data architecture, supporting data integration pipelines, and resolving data quality issues. Ideal candidates will have over three years of relevant experience, along with proficiency in SQL and Python. The role is based in West London, offering competitive salary and a range of benefits including equity options and medical insurance.

Benefits

Flexible working hours

Stock options

Medical insurance, including dental

Life and critical illness insurance

Monthly credit for Wheely journeys

Lunch allowance

Professional development subsidies

Cycle to work scheme

Top-notch equipment

Relocation allowance

Qualifications

• 3+ years of experience in Data Infrastructure Engineer/Data Engineer/MLOps Engineer roles.
• Fluent in SQL and Python.
• Intermediate level of English.
• Experience with open-source technologies for data ingestion and BI reporting.

Responsibilities

• Enhance Data team with architectural best practices.
• Support evolving data integration pipelines and data modelling.
• Cover business units' feature requests/bugfixes/data quality.

Skills

SQL

Python

Team work (GitOps, Continuous Integration)

Analytical Databases

Data Pipelines

Containerizing applications and code (Docker, k8s)

Education

Technical university degree

Tools

Snowflake

Redshift

BigQuery

Kafka

Airflow

Job description

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
• Fluent with SQL and Python;
• At least Intermediate level of English;
• Have experience in researching and integrating open-source technologies (data ingestion, data modelling, BI reporting, LLM applications, etc.);
• Ability to identify performance bottlenecks;
• Team work: GitOps, Continuous Integration, Code reviews;
• Technical university graduate.

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 & equity package
• Medical insurance, including dental
• Life and critical illness insurance
• Monthly credit for Wheely journeys
• Lunch allowance
• Professional development subsidies
• 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.

All of your personal information will be collected, stored and processed in accordance with Wheely’s Candidate Privacy Notice