Senior Data Engineer

Description

The company runs a data platform, and this hands-on senior role builds and improves the pipelines the business depends on.

You will design and ship dependable, well-tested pipelines that follow the team's existing roadmap, and help the team release work in a steady, repeatable way.

You will follow the company's data governance rules when handling sensitive information. You will work with Analytics, Data Science, Software Engineering and IT/Infrastructure, and talk with people across the business to learn what they need, define scope and find pain points, then explain your work plainly.

Responsibilities

• Build sturdy, scalable data pipelines using Snowflake, dbt, Airflow and Python.
• Improve existing pipelines so they scale better and fail less often.
• Investigate production incidents and fix their root causes rather than applying quick patches.
• Apply test-driven development, monitoring, logging and observability in your work.
• Create reusable frameworks and methods that help the team work consistently.
• Stay within established patterns and the platform roadmap, and propose practical improvements where you see them.
• Use CI/CD tooling and controlled release steps to test and deploy changes safely.
• Pass useful practices on to other data engineers.
• Help make data quality and lineage good enough that any figure can be traced back to its source.
• Handle sensitive data correctly under the governance framework, including care over what data goes into AI tools.
• Gather requirements from across the business, clarifying scope and pain points.
• Demo your work to colleagues and explain it in clear, practical terms.
• These statements describe the general nature and level of the work. They do not list every duty.

Requirements

• A degree or equivalent, typically with 7+ years of relevant experience.
• Bachelor's degree level or above.
• 4+ years of data engineering experience.
• Advanced SQL and Python, with hands-on experience building and running data pipelines.
• Hands-on work with Snowflake, dbt and Airflow, or a comparable modern data stack.
• Hands-on experience with CI/CD pipelines and controlled releases, including automated testing.
• Experience with test-driven development, monitoring, and fixing production issues.
• Experience on a cloud data platform.
• Clear communication, including gathering requirements from colleagues who are not technical.
• Desirable: Databricks and PySpark.
• Desirable: exposure to Infrastructure as Code or containerised environments.
• Desirable: a measured, thoughtful approach to new tools, including AI, with attention to governance, ethics and protecting confidential data.

Conditions

This is a hybrid role based in the UK, with two days per week expected on site.

You must already have the right to work in the UK. Sponsorship is not offered for this role.