Senior Data Engineer

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About the role

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. Why we’re hiring We’re growing the data engineering capability behind ad-tech solutions that process large-scale, real-time audience data. In this role, you’ll take deep technical ownership of the data model that supports targeting and measurement decisions for advertisers at scale. You’ll help evolve a complex, interconnected data platform while working with modern distributed processing technologies and a highly collaborative engineering team. Who you’ll be working with You’ll work closely with data engineers and colleagues across Quality Assurance, Analytics and connector teams. We value teamwork over ego, collaboration over competition, open and honest communication, strong opinions held with curiosity, and continuous improvement through kaizen. Our technology environment • Scala-based backend services • Google Cloud Platform (GCP) • Apache Spark for large-scale distributed data processing • Parquet and BigQuery • Tyda, an open-source, automation-driven software development lifecycle process What you’ll do • Own and evolve a core data model spanning input and output models, field types and partitioning strategies across multiple pipeline stages. • Maintain and extend a multi-layered audience segmentation framework, normalising raw data into standardised and canonical representations across dimensions such as location, age, gender, interests and brand affinity. • Work across a broad modelling surface, including audience types, behavioural signals, relational structures, embeddings and anomaly detection. • Develop and maintain Spark-based data jobs in an environment using Scala, GCP, Parquet and BigQuery, with a clear understanding of end-to-end data flow. • Partner with Quality Assurance, Analytics and connector teams to ensure data correctness, integrity and reliable downstream use. • Write production-ready code that is readable, testable, performant and resilient to edge cases and failures. • Contribute to team practices, continuous improvement and constructive peer feedback while taking ownership of data quality and engineering standards. What you’ll need • 5+ years of experience in data engineering, with a strong record of delivering complex, multi-layer data pipelines. • Experience with Scala or a similar strongly typed or advanced functional programming language; you’re comfortable reasoning about complex type systems and willing to develop further in Scala. • Experience with Apache Spark and large-scale distributed data processing. • 3+ years of experience with GCP and big-data stores such as BigQuery. • The ability to build a clear mental model of a large, interconnected data domain and reason about how changes in one area affect others. • Strong communication skills, with the ability to explain complex data models and technical decisions to both technical and non-technical stakeholders. • Experience with data monitoring, detection, troubleshooting and validation framew

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