Role Overview

Reporting to the Data & Analytics Lead, the Principal Data Engineer is a hands-on role, combining the building and optimisation of production data pipelines with the technical leadership needed to raise engineering standards and develop the people around them. The role functions as a key interface between a) business stakeholders and department heads, b) the wider data and analytics team, and c) owners of source systems and data in Finance and IT.

Key Responsibilities

Designing and building robust, production-grade data pipelines on Databricks, making appropriate use of current platform capabilities such as Spark Declarative Pipelines (SDP)
Working “under the hood” to optimise the platform for performance and cost — tuning compute, jobs and queries, managing storage and table layout, and keeping platform spend under control
Defining and maintaining consistent business metrics and a semantic layer (for example, using Metric Views) so reporting is built on trusted, reusable definitions
Integrating data from core business systems, including SAP S/4HANA, and other sources, using tools such as Fivetran (both SaaS connectors and HVR)
Setting and upholding engineering standards across the team — code quality, testing, documentation, CI/CD and data governance
Coaching and mentoring junior and mid-level engineers, reviewing their work and helping them develop
Partnering with business stakeholders to understand their needs, shape practical solutions and ensure the platform delivers genuine value
Engaging data owners in Finance and IT to ensure data is well understood, valid and fit for purpose, and initiating data quality improvements where required

Requirements

Skills & Experience

Experience

At least 3 years of hands-on, daily Databricks experience, covering both pipeline development and under-the-hood performance and cost optimisation
Up to date with recent platform developments, such as Spark Declarative Pipelines (SDP) and Metric Views
Strong proficiency in programming languages commonly used in data engineering, such as Python, SQL and Spark
Advanced experience with data manipulation, data modelling, database design and query optimization
Experience managing or coaching junior developers
A track record of managing and influencing business stakeholders
Experience working with SAP S/4HANA data sets, Fivetran (including both SaaS connectors and HVR), Power BI semantic modelling would be beneficial

Key Competencies

Combining deep, hands-on engineering skill with sound judgement about cost, performance and long-term maintainability
Coaching, mentoring and raising the capability of less experienced engineers
Collaborating, communicating confidently and influencing business stakeholders
Breaking down complex technical concepts and explaining them simply to non-technical audiences
Staying current with a fast-moving platform and bringing new capabilities into everyday practice
Taking ownership and driving work independently, from concept through to production

Important to note:

This role requires full-time office-based attendance, five days per week.

To apply

Qualified candidates to apply by uploading a cover letter and a recent resume by close on business 31 July 2026.