Principal Data Engineer

About the role

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 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 .

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