Senior Data Engineer

WPP is the trusted growth partner for the world’s leading brands. With exceptional talent, trusted data and intelligence, and world-class partnerships – all united by our pioneering agentic marketing platform, WPP Open – we help clients navigate change, capture opportunity, and deliver transformational growth. 

WPP Media is WPP's AI-driven media operating unit, bringing together media, data, and partnerships to deliver creative personalisation at scale. Connected through WPP Open and powered by Open Intelligence, clients see exactly where, how, and why their media investment is working.

For more information, visit wppmedia.com.

We are looking for a skilled and motivated Sn Data Engineer to join our global team. You are a hands-on builder who is passionate about creating robust, scalable data solutions that solve real-world problems. You will be a key contributor to the team, responsible for designing, developing, and maintaining the data pipelines and infrastructure that are the foundation of our analytics products. In return providing value to our clients.

Working closely with the VP of custom reporting and other engineers in the team, you will execute the technical roadmap, transforming complex business requirements into high-quality, reliable data assets. If you thrive on turning massive datasets into actionable intelligence and enjoy working with cutting-edge cloud technologies, this role is for you.

• →Design, build, and maintain scalable and reliable data pipelines and infrastructure, primarily using Google Cloud Platform (GCP) services like BigQuery and Cloud Storage, and Snowflake.
• →Develop, test, and deploy data transformation logic using SQL and DBT (data build tool) to create clean, reliable, and performant data models.
• →Collaborate with analytics, product, and engineering teams to understand data requirements and translate them into technical specifications.
• →Implement and uphold data quality and governance processes to ensure the accuracy, consistency, and integrity of our datasets.
• →Contribute to the execution of the data engineering roadmap by delivering on key initiatives and projects.
• →Develop and maintain monitoring for data pipeline performance, identifying and resolving issues to ensure data availability and freshness.
• →Optimize data pipelines and queries for performance, scalability, and cost-effectiveness.
• →Support data consumers by exposing data through APIs and supporting integrations with analytics and visualization tools like Power BI.
• →Create and maintain technical documentation for data pipelines, models, and processes to support product adoption and team knowledge sharing.
• →Contribute to a collaborative team environment, participating in code reviews and sharing your expertise with fellow engineers.

• Proven experience as a Data Engineer, with a track record of building and maintaining production-level data pipelines and ETL/ELT processes.
• Strong proficiency in SQL and experience with data manipulation languages for complex data transformation and analysis.
• Hands-on experience with cloud data platforms, ideally Google Cloud Platform (GCP), including services like BigQuery and Cloud Storage.
• Experience with DBT (data build tool) for building modular, scalable, and testable data models, or equivalent.
• Strong understanding of data modelling concepts, data warehousing principles, and data integration techniques.
• Proficiency with a programming language such as Python for scripting and data pipeline development.
• Digital advertising familiarity: An understanding of campaign data from platforms like Google Ads, Facebook Ads, or DSPs is a strong plus.
• Analytical mindset and problem-solving skills: You can troubleshoot complex data issues and develop robust, long-term solutions.
• Excellent collaboration skills: You can communicate effectively and work well in a team-oriented environment with various technical and non-technical stakeholders.
• Experience working in an Agile development environment.
• Experience supporting data visualization tools (e.g., Power BI) is desirable.