Senior Data Engineer

Overview

As a Senior Data Engineer, you will own and shape a scalable data platform built on Databricks, delivering trusted data products and self-serve access for the business. You’ll work closely with cross-functional teams to translate challenges into data solutions and help mature the data function. This role offers visible impact on architecture and platform strategy in a growing data organisation. You’ll join a collaborative, hands-on team at a pivotal stage of our Data Ops journey.

Pay / Benefits

• health insurance
• income protection
• life assurance
• subsidised gym membership
• 25 days holiday plus birthday off

Responsibilities

• Design, build and maintain scalable data pipelines and data products using Databricks, PySpark, Spark SQL and Delta Lake
• Develop and optimise ETL/ELT processes to ingest, transform and curate data from internal and external systems
• Shape enterprise data architecture balancing scalability, performance, security and maintainability
• Partner with Finance, Product, Sales, Marketing and Engineering to translate business challenges into technical solutions
• Embed data quality, governance and access controls throughout the data lifecycle
• Mentor a junior engineer and help mature a growing data function

Key requirements

• Senior level data engineering experience with strong Databricks skills (PySpark, Spark SQL, Delta Lake)
• Advanced SQL and Python coding
• Track record of building and optimising enterprise-scale data pipelines and ETL/ELT solutions
• Solid grounding in data architecture, modelling and modern data platform design
• Cloud experience (AWS preferred; Azure also acceptable) and familiarity with CI/CD and source control
• Experience across multiple data pools, with focus on financial & sales / revenue data preferred

• Stakeholder collaboration
• Mentoring and team growth
• Problem solving and adaptability
• Databricks
• PySpark
• Spark SQL

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