Data Engineer

• 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

• 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.

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.

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.