Quick Summary
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…
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…
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:
What We Offer
~1 min readLocation & Eligibility
Listing Details
- Posted
- May 15, 2026
- First seen
- May 16, 2026
- Last seen
- May 18, 2026
Posting Health
- Days active
- 0
- Repost count
- 1
- Trust Level
- 61%
- Scored at
- May 16, 2026
Signal breakdown
Please let Wpp know you found this job on Jobera.
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