Data Engineer

Summary

Join our Engineering team in London as a Data Engineer and contribute to building the world's leading research platform. You will design, develop, deploy, and support data infrastructure, pipelines, and architectures. Responsibilities include writing clean, efficient code for data pipelines, managing AWS data infrastructure (including Redshift and Airflow), and ensuring system performance and scalability. You will also mentor junior engineers and leverage learning and development opportunities to enhance your skills. This role requires a STEM degree or equivalent experience, 3+ years of data engineering experience with Python and SQL, and expertise in DataOps methodologies and AWS data services. A proven track record of success and a proactive, meticulous approach are essential.

Requirements

• You have a degree in a STEM subject , but we’re happy to work with people who perfected their craft via a different route
• 3+ years of hands-on data engineering development experience, with deep expertise in Python , SQL , and working with SQL/NoSQL databases
• Skilled in designing, building, and maintaining data pipelines , data warehouses , and leveraging AWS data services
• Strong proficiency in DataOps methodologies and tools, including experience with CI/CD pipelines, containerized applications , and workflow orchestration using Apache Airflow
• Proven track record – You’ve made a demonstrable impact in your previous roles, standing out from your peers. We’re looking for people who have incredible potential
• Highly driven and proactive – you relentlessly and independently push through hurdles and drive towards excellent outcomes
• Meticulous – you hold high standards and have an obsessive attention to detail

Responsibilities

• Design solutions: Design, develop, deploy and support data infrastructure, pipelines and architectures, contributing to an architectural vision that will scale up to be the world's leading research platform
• Ship working code: Write clean, efficient, and maintainable code that powers data pipelines, workflows, and data operations in a production environment. Implement reliable, scalable, and well-tested solutions to automate data ingestion, transformation, and orchestration across systems
• Own data operations infrastructure: Manage and optimise key data infrastructure components within AWS, including Amazon Redshift, Apache Airflow for workflow orchestration and other analytical tools. You will be responsible for ensuring the performance, reliability, and scalability of these systems to meet the growing demands of data pipelines and analytics workloads
• Build your competency: You will learn quickly by building market-leading technology with experienced colleagues in a high performance environment. Engineers can also use our L&D budget to fast-track development of specific technical competencies
• Maintenance and troubleshooting: Your role will include overseeing configuration, monitoring, troubleshooting, and continuous improvement of our infrastructure to support delivering high-quality insights and analytics

Preferred Qualifications

Familiar with ETL frameworks, and bonus experience with Big Data processing (Spark, Hive, Trino), and data streaming

Benefits

Engineers can also use our L&D budget to fast-track development of specific technical competencies