Senior Data Engineer
WPP is hiring a Senior Data Engineer in London, United Kingdom. Level rates it ; you can apply on WPP.
Level's read on this job
- Level rates this data engineer role Little AI ●○○○: aI is not part of the work.
- The posting allows some remote work.
- Tools and skills the posting cites include AWS, Google Cloud and Azure.
- Level classifies it as a senior role.
- Level lists 210 other open roles at WPP.
AI in this role
Engineering manager leading data engineering teams to build scalable pipelines and data infrastructure.
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 are seeking an experienced and visionary Engineering Manager to lead one of our data engineering team. In this role, you will be responsible for managing and scaling data products, driving data pipeline development, and ensuring the availability, quality, and security of our data assets. You will collaborate closely with cross-functional teams including data scientists, analysts, product managers, and software engineers to enable data-driven decision-making across the organization.
What you'll be doing:
- Lead, mentor, and grow a high-performing team of data engineers.
- Design, build, and maintain scalable, reliable, and efficient data pipelines and architectures.
- Oversee the development and implementation of ETL/ELT processes, data warehousing, and data lake solutions.
- Collaborate with stakeholders to understand business requirements and translate them into technical data solutions.
- Ensure data quality, consistency, and security across all data engineering workflows.
- Define best practices and standards for data engineering and promote their adoption.
- Drive continuous improvement in data infrastructure and tooling, leveraging cloud platforms (e.g., AWS, GCP, Azure) and big data technologies (e.g., Spark,dbt).
- Collaborate with PMs to manage project timelines, resource allocation, and deliverables to meet business goals.
- Work with data governance and compliance teams to ensure data privacy and regulatory compliance.
- Stay updated with the latest data engineering trends and technologies and evaluate their applicability.
What you'll need:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
- 7+ years of experience in data engineering or software engineering roles, with at least 3 years in a leadership/management position.
- Strong expertise in data pipeline development, ETL/ELT processes, and data warehousing solutions.
- Proficient with cloud platforms (AWS, GCP, Azure) and big data tools like Apache Spark, Python, etc.
- Experience with relational and NoSQL databases.
- Solid understanding of data modeling, data architecture, engineering frameworks
- Proven ability to lead and scale engineering teams and manage cross-functional projects.
- Excellent problem-solving skills and ability to communicate complex technical concepts to both technical and non-technical stakeholders.
- Experience with agile development methodologies.
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 believe in the power of creativity, technology and talent to create brighter futures or our people, our clients and our communities. We approach all that we do with conviction: 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 aim to create a culture in which people can do extraordinary work.
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. Are you up for the challenge?
#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
Senior Data Engineer at WPP rates 30 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.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- Typical data engineer job
- $150k
This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs
Questions you could be asked
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where etl was part of your work. What did you do?
- Tell me about a project where data warehousing was part of your work. What did you do?
- Tell me about a project where team management was part of your work. What did you do?
- Tell me about a project where pipeline development was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Data Engineering, ETL, Data Warehousing, Team Management, and Pipeline Development. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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