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.

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.

As a Data Engineer in the WPP Enterprise Data Group, you will be responsible for the design and implementation of scalable data solutions providing enterprise-scale data transformation across a broad range of projects.
Your role will focus on delivering solutions that utilize large-scale data ingestion, processing, storage/querying, streaming, and batch analytics using Databricks . As part of a team, you will implement world-class solutions designed by our data architects. Your responsibilities will include estimating, designing, coding, testing, deploying, and ensuring scalability and performance on Azure using key technologies like Databricks.
As a hands-on technologist with an extensive data engineering background using Databricks , you will be joining a group of Data Engineers who are passionate about building the best possible solutions for our business and endorse a culture of life-long learning and collaboration.
Design, build, test and maintain data pipelines (ELT), according to business and technical requirements.
Implement secure platforms with data governance in mind.
Play a key role in automation and building industry leading solutions against architectural best practices.
Deliver data migrations between legacy & modern platforms
Design & deliver data warehousing solutions and key data engineering workstreams for any required solution.
Support cross-functional teams across the data space.
3+ years of experience designing and building scalable distributed data pipelines and dimensional data models

3+ years of experience in Python and SQL
Experience using Databricks platform and PySpark is a must.
Extensive experience of Microsoft Azure data services – Data Factory, ADLS gen2, Event Hubs, Azure SQL, Azure Key Vault
Ideally experience in the following – Kafka, Delta Lake, Pandas
A demonstrable understanding of Continuous Integration, Continuous Delivery (CI/CD) and Agile practices, unit & integration tests and development practices using Azure DevOps.
Fluency in English.
Exposure to AI & ML technologies is a plus.

We believe in the power of creativity, technology and talent to create brighter futures or our people, our clients and our communities. We are creative leaders and pioneers of our industry; Scale and opportunity – We offer the opportunity to create, influence and complete projects at a scale that is unparalleled in the industry.
Challenging and stimulating work – Unique work and the opportunity to join a group of creative problem solvers. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process.
We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.

Data Engineer AI, Hybrid

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