Data Engineer

📍 London | 🏢 2 days per week in office

Data Engineering Team 🚀

The Data Platform team is responsible for designing, building, maintaining, and optimising our modern data platforms and infrastructure. Our main goal is to ensure the organisation has seamless access to high-quality, reliable, and performant data, from ingestion through to consumption by various teams. We work on key projects involving data pipeline development, platform management, model training and deployment, data quality assurance and customised data tooling.

What You'll Be Doing 🗃️

• Design, build, and maintain scalable and resilient data pipelines and infrastructure, using Python for custom data transformations, API integrations, and orchestration.
• Implement and manage data platforms leveraging Kubernetes for efficient deployment, orchestration, and scaling of data services and applications.
• Own the flow and security of data in our Snowflake data warehouse, ensuring optimal data delivery architecture and availability for global business operations and data science work.
• Build CI/CD pipelines using GitHub for automated testing, deployment, and version control.
• Collaborate with stakeholders across Engineering, Data Science, and Analytics Engineering to gather requirements and deliver high-impact data solutions.
• Ensure data quality, reliability, and observability across the platform through robust monitoring, alerting, and testing frameworks.

Our Values & Culture 🌞

• Just Pilot: We never settle for "good enough". We pilot new ideas fast, ask questions to figure it out, and scale quickly.
• Why Not Today? Fast is as slow as we go - speed and simplicity gives us a competitive advantage.
• Be a Buddy: We tap in from day one to help the team, we do the right thing even if it's hard.
• Owners and Dates: We don't chase people. If you own a task and agree to a date, the expectation is that it gets done.
• Feedback: We want our employees to flourish, so we regularly provide direct and constructive feedback.

We're Looking For 🔎

• Proven experience as a Data Engineer, designing, building, and maintaining scalable data platforms and pipelines.
• Deep experience with Snowflake, including advanced features like dynamic data masking, row-level security, data backups, and ELT tools.
• Strong Python skills for data engineering, scripting, and automation.
• Strong SQL performance, with a solid understanding of data warehousing concepts.
• Demonstrated experience with GitHub, CI/CD, and collaborative development.
• Strong stakeholder management and communication skills, comfortable working with technical and non-technical colleagues.
• Experience in kubernetes, datadog and ML model deployments are great to have.

Interview Process 🤝

• First stage: 30 minute intro and values call with Talent Partner (Video call).
• Second stage: 60 minute CV overview with Head of Data Platform & Team Manager (Video call).
• Final stage: Split into two parts - Part 1: 60 minute technical assessment with 2 members of the Data Engineering team. Part 2: 30 minute chat with the rest of the team (Virtual).

Diversity & Inclusion 🌈