Data Engineer

At Wheely, we're a luxury brand on the outside, but a technology company on the inside, building the world's first Luxury-as-a-Service. We believe that time is the ultimate luxury and that modern engineering and design, combined with the industry’s highest standards of service, can unlock an unparalleled experience for our customers. From on-demand chauffeuring, concierge service, to our best-in-class app, we exist to help our clients reclaim their time by connecting them to the places and people that matter.

More than 40% of our team works in product & engineering, and both Wheely founders are technical. We are also unapologetically design centric. It’s not about A/B testing one hundred shades of blue, but crafting the perfect shade. We also take a privacy-first approach and believe that where people travel, and who they travel with, is at their discretion.

We have refused government requests to hand over journey data, and are currently developing bespoke technology to put our clients’ movements beyond even our own reach.

Backed by leading global investors, Wheely is poised for the next phase of our journey. Over the next 5-10 years, we plan to offer a full portfolio of luxury services and expand into more international cities, building on our success in London, Paris, and Dubai.

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.

• Competitive salary
• Employee stock options plan
• Relocation allowance
• Lunch allowance
• Medical insurance, including dental
• Best-in-class equipment
• Professional development subsidies
• Wheely has an in-person culture but allows flexible working hours and work from home when needed

Wheely is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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