Level

WPP

Data Engineer

AI in this role

databricks

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:

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.

What you'll be doing:

  • 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.
  • Propose technical designs and develop integrations.
  • 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.

What you'll need:

Minimum requirements for this role include:

  • 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.

Who you are:

You're open: we are inclusive and collaborative; we encourage the free exchange of ideas; we respect and celebrate diverse views. We are open-minded: to new ideas, new partnerships, new ways of working.

You're optimistic: we approach all that we do with confidence: to try the new and to seek the unexpected.

You're extraordinary: We are stronger together: through collaboration we achieve the amazing. We are creative leaders and pioneers of our industry; we provide extraordinary every day.

What we'll give you:

Passionate, inspired people – we champion a culture of people that do extraordinary work

Scale and opportunity – we offer the opportunity to create, influence and deliver 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. 

 

#LI-Hybrid 

We believe the best work happens when we're together, fostering creativity, collaboration, and connection. 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.

WPP is an equal opportunity employer and considers applicants for all positions without discrimination or regard to particular characteristics. 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.

Please read our Privacy Notice (https://www.wpp.com/en/careers/wpp-privacy-policy-for-recruitment) for more information on how we process the information you provide.

How we rate this

Data Engineer at WPP rates 23 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

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