Senior Data Engineer

About the role

We're looking for a Senior Data Engineer to join our Data and Insights team. You'll be hands‑on every day, writing production code, building and maintaining data pipelines, and shipping features that turn raw data into intelligence our clients can act on. You'll work across the full project lifecycle, from understanding the problem through to delivery, and you'll care as much about code quality and operational reliability as you do about getting things shipped.

Key responsibilities

• Write production code every day, most likely in Python, building and maintaining the data pipelines that power our Insights products.
• Own the full lifecycle of your projects, from understanding the data domain through to pragmatic design, shipping, and keeping things running reliably in production.
• Set and lead the technical direction of the Insights platform, and communicate it openly across engineering and the wider business.
• Help raise engineering standards across the team and improve technical quality through testing, observability, data quality checks, and clean, maintainable code.
• Make AI your default way of working and find opportunities to apply it across our products and pipelines where it delivers real value.
• Help lay the foundations for our emerging MCP and semantic layer so our data becomes something both people and AI systems can query and reason over.

Required profile

• Strong software engineering fundamentals: you write well‑tested, production‑ready Python and care about maintainability, observability, and operational excellence.
• A track record of building data pipelines and production systems from the ground up, not just configuring managed services.
• Solid experience with modern data engineering tools and patterns, with depth in SQL, Spark, Databricks/Delta Lake, orchestration tools (Dagster, Airflow, Temporal), and dbt.
• Comfort with modern deployment practices: CI/CD, containerisation (Docker), and cloud‑based infrastructure.
• A product mindset: you understand the business domain and shape what gets built, not only how.
• Strong communication skills: you can explain and build support for your ideas with technical and non‑technical stakeholders.
• AI as a default part of how you work, with evidence of real efficiency gains and creative use beyond code generation.

Required skills

• Python
• SQL
• Spark
• Databricks
• Delta Lake
• Dagster
• Airflow
• Temporal
• dbt
• CI/CD
• Docker
• Cloud infrastructure