Requirements

• 2+ years of experience as a Data Engineer working on data platforms, ideally in product-led or high-growth environments.
• Experience building and operating ETL/ELT pipelines.
• Hands-on experience with modern data stacks including some of the following or similar technologies: Python, SQL, Snowflake, Apache Iceberg, AWS S3, PostgresDB, Airflow, dbt, Apache Spark, AWS, Docker, Terraform.
• Ability to work effectively with teammates and stakeholders.
• Pragmatic approach to balancing quality with delivery needs.
• Eagerness to learn, take feedback, and grow technical skills.
• AI-first mindset: curiosity, fast experimentation, and ownership in leveraging AI tools daily.

Nice to Haves

• Familiarity with Data Mesh or Lakehouse architectures.
• Familiarity with Kubernetes, Docker, and real-time streaming technologies such as Kafka or Kinesis.
• Exposure to ML engineering pipelines or MLOps frameworks.

What You'll Be Doing

• Build, maintain, and improve scalable, reliable, and secure data pipelines and related systems.
• Follow and uphold best practices in data engineering including testing, CI/CD, observability, and infrastructure as code.
• Participate in code reviews and team knowledge sharing.
• Build and maintain data pipelines, warehouses, and streaming systems within the existing architecture.
• Model and structure data to meet analytics, data science, and operational requirements.
• Contribute to improvements in data systems and tooling.
• Collaborate with teams across the business to translate requirements into reliable technical solutions.
• Identify opportunities for optimisation and tooling improvements.
• Deliver against the technical roadmap for data engineering.

Perks and Benefits

• Market-competitive salary, benchmarked annually against the function.
• Annual performance bonus linked to company performance and individual contribution.
• Share options providing ownership and a stake in the company’s future.
• Private medical insurance.
• Pension plan, generous holiday allowance, and £1,000 yearly budget for commuting or learning.
• Access to cutting-edge systems and tools to maximize impact.