Data Engineer
Role details
Job location
Tech stack
Job description
As a Data Engineer within the Platform team, you will play a critical role in maturing and optimizing our Data Lake. Acting as a key bridge between Platform and Data Science, you will take ownership of the infrastructure and pipelines that power data-driven decision-making across the business. This is an Individual Contributor (IC) role with high impact and autonomy.
In your first 6-12 months, your primary focus will be to evolve the Data Lake into a scalable, high-performance foundation for analytics and data science. You will migrate key production workloads- such as model calibration, ad-hoc analytics, and reporting- directly into the Data Lake, while redesigning data structures to improve query performance, reduce AWS costs, and ensure high data recency. You will also establish yourself as a trusted partner to the Data Science team, enabling faster experimentation and delivery through robust, well-designed data systems.
Technology Stack
- Cloud & Compute: AWS, ECS Fargate, AWS Lambda
- Databases & Data Lake: Aurora (PostgreSQL, MySQL), Athena, DMS, Glue, Iceberg
- Languages & IaC: Python, Spark, SQL
- Observability & Tooling: Amazon Managed Prometheus (AMP), incident.io, GitLab
What you'll be doing
- Own and evolve the Data Lake infrastructure and ETL pipelines from day one
- Migrate production workloads (e.g. model calibration, ad-hoc analytics, reporting) into the Data Lake
- Partner closely with Data Science to understand workflows and enable scalable, efficient data usage
- Redesign data structures and clustering strategies to improve query performance and data freshness
- Optimize infrastructure to reduce AWS costs while maintaining reliability and scalability
- Build robust, production-grade data systems using modern AWS tooling
Requirements
- Strong software engineering foundation with applied knowledge of SOLID principles in data systems
- Proven experience building and maintaining Change Data Capture (CDC) pipelines, ideally with AWS DMS
- Hands-on expertise with Spark and AWS Glue, including transforming RDS workloads into scalable pipelines
- Highly proficient in SQL, particularly within transactional RDS environments
- Experience implementing governance, standards, and best practices across data platforms
- Comfortable owning systems end-to-end and working cross-functionally with technical stakeholders
How we work
- Ownership: You take responsibility for outcomes, not just tasks
- Impact-Driven Work: You focus on results and step up during critical moments when needed
- MVP Mindset: You prioritize speed and learning, accepting and managing technical debt when appropriate
- Collaboration: You go beyond your role and avoid siloed thinking
- Adaptability: You thrive in a fast-moving environment with shifting priorities
- Pragmatism: You value sound judgment and lightweight processes over rigid bureaucracy
Benefits & conditions
- Everyone owns a piece of the company - equity
- Hybrid with 3 days a week in the office
- 25 days' holiday a year, plus 8 bank holidays
- 2 paid volunteering days per year
- One month paid sabbatical after 4 years
- Employee loan
- Free gym membership
- Team wellness budget to be active together - set up a yoga class, a tennis lesson or go bouldering