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 experience.
Responsibilities
Enhance Data team with architectural best practices and low-level optimizations Help refactor and improve codebase (dbt for data transformations, LookML for semantic layer) Support on evolving Data Integration pipelines (Airbyte, Debezium, Kafka), Database engines (Snowflake), BI tools (Looker, Metabase), 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 / Analytics Engineer roles; Have work experience or troubleshooting experience in the following areas: Data Pipelines: deployment, configuration, monitoring (Airbyte, Debezium, Airflow) Analytical Databases: configuration, troubleshooting (Snowflake, Redshift, BigQuery, Clickhouse or similar) Data Modeling: DRY and structured approach, applying performance tuning techniques Containerizing applications and code: Docker, devcontainers
Fluent with SQL and Python; At least Intermediate level of English; Have experience in researching and implementing technologies; 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.
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Enhance Data team with architectural best practices and low-level optimizations Help refactor and improve codebase (dbt for data transformations, LookML for semantic layer) Support on evolving Data Integration pipelines (Airbyte, Debezium, Kafka), Database engines (Snowflake), BI tools (Looker, Metabase), 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 / Analytics Engineer roles; Have work experience or troubleshooting experience in the following areas: Data Pipelines: deployment, configuration, monitoring (Airbyte, Debezium, Airflow) Analytical Databases: configuration, troubleshooting (Snowflake, Redshift, BigQuery, Clickhouse or similar) Data Modeling: DRY and structured approach, applying performance tuning techniques Containerizing applications and code: Docker, devcontainers
Fluent with SQL and Python; At least Intermediate level of English; Have experience in researching and implementing technologies; 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.
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