Job Description

Reporting to the Data & Analytics Lead, the Principal Data Engineer is a hands-on role, combining the building and optimization 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 business stakeholders and department heads, the wider data and analytics team, and the owners of source systems and data in Finance and IT. Requirements KEY RESPONSIBILITIES: Design and build robust, production-grade data pipelines on Databricks, making appropriate use of current platform capabilities such as Spark Declarative Pipelines (SDP). Work “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. Define and maintain consistent business metrics and a semantic layer (for example, using Metric Views) so that reporting is built on trusted, reusable definitions. Integrate data from core business systems, including SAP S/4HANA, and other sources, using tools such as Fivetran (both SaaS connectors and HVR). Set and uphold engineering standards across the team, including code quality, testing, documentation, CI/CD and data governance. Coach and mentor junior and mid-level engineers, review their work and help them develop. Partner with business stakeholders to understand their needs, shape practical solutions and ensure the platform delivers genuine value. Engage data owners in Finance and IT to ensure data is well understood, valid and fit for purpose, and initiate data quality improvements where required. REQUIRED SKILLS AND EXPERIENCE: At least three years of hands-on, day-to-day 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 optimisation. Experience managing or coaching junior developers. A track record of managing and influencing business stakeholders. 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. NICE TO HAVE: Experience working with SAP S/4HANA data sets. Experience with Fivetran, including both SaaS connectors and HVR. Power BI semantic modelling experience. QUALIFICATIONS: A relevant tertiary qualification in Computer Science, Information Systems, Engineering or a related field, or equivalent practical experience.