Data Engineer

Wheely; Greater London; On-site; GBP 50,000 - 70,000; Full time

Job summary

A cutting-edge transport company in Greater London seeks a Data Engineer to join their Data Team. In this role, you will enhance data integration and pipelines, implement best practices, and ensure data quality while collaborating with various teams. The ideal candidate has extensive experience in data engineering and analytical databases, and is fluent in SQL and Python. This office-based position offers flexible working hours, a competitive salary and equity package, alongside a comprehensive range of perks and benefits.

Benefits

Flexible working hours

Stock options

Medical insurance

Life insurance

Lunch allowance

Cycle to work scheme

Qualifications

• 3+ years of experience in Data Engineering and MLOps roles.
• Experience in troubleshooting and configuring analytical databases.
• Fluent in SQL and Python with a solid understanding of data modeling.

Responsibilities

• Enhance Data team with architectural best practices.
• Support evolving data integration pipelines using various tools.
• Enforce code quality and automated testing.

Skills

Data Infrastructure Engineer

SQL

Python

Docker

GitOps

Continuous Integration

Analytical Databases

Education

Technical university graduate

Tools

Snowflake

Kafka

Airflow

BigQuery

Redshift

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 allowanceProfessional 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