Level

WPP

Senior Data Engineer

AI in this role

databricks
rag

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:

 Our organization is embarking on a transformative journey to unify our global data landscape through a new central initiative. We are moving away from fragmented systems to a standardized, cloud-agnostic, and AI-ready data platform built on a modern tech stack: dbt, Databricks, Python (dlt), and GitHub Actions. 

As a foundational member of our central platform team in Chennai, you will be a hands-on builder responsible for bringing our strategic data blueprint to life. This is a role for an execution-focused engineer who loves building high-quality, governed, and reusable data assets that will be deployed across our global markets and wants to make a tangible impact on a global scale. This role combines data engineering along with an opportunity to enable next-generation AI.

What you'll be doing:

  • Develop, test, and deploy robust, scalable, and optimized data transformation pipelines using dbt and SQL on the Databricks platform. 
  • Design and maintain scalable dimensional models (SCD1/SCD2), implement advanced partitioning, and ensure high-performance query execution. 
  • Enforce and automate data governance, data quality checks, and security (RLS/CLS) using Databricks Unity Catalog and dbt's testing framework. 
  • Implement and manage data ingestion from diverse sources (REST APIs, SFTP, SQL databases, Cloud Storage) using Python, preferably with frameworks like dlt. 
  • Leverage the full potential of the Databricks Lakehouse Platform, with a focus on Databricks SQL and Unity Catalog for governance, security (RLS/CLS), and data discovery. 
  • Design and build data products that support Agentic AI and Generative AI applications, ensuring reliable, governed, and low-latency access to enterprise data.
  • Partner with DevOps teams to establish and maintain CI/CD pipelines for data projects using GitHub Actions for automated testing and deployment 
  • Document solutions clearly and contribute to operational runbooks and knowledge base. 
  • Collaborate with global teams to execute the strategic blueprint, ensuring standards and best practices are followed across markets. 
  • Mentor junior and mid-level engineers through code reviews, pair programming, and technical guidance 

What you'll need:

  • Experience: 5+ years of dedicated, hands-on data engineering experience, with a strong track record of delivering production-grade solutions 
  • dbt Expertise: Expert-level proficiency in dbt (Core), including structuring projects, writing macros, implementing tests, and integrating with CI/CD. This includes experience of resolving real production issues and versed with the best-practices around the same.  
  • Databricks Proficiency(with focus on SQL) : Strong, practical experience with the Databricks Lakehouse Platform, specifically Databricks SQL, Unity Catalog, and Databricks Workflows.  Good understanding of Delta Lake , Performance Optimization techniques. 
  • Understanding of Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, vector databases, and semantic layers. Ability to collaborate with AI teams and prepare enterprise data for GenAI use cases.
  • Python for Data Engineering: Proficient in Python for data ingestion and automation. Experience with data loading libraries is a major plus. 
  • SQL & Data Warehousing Mastery: Deep understanding of advanced SQL, query optimization, MPP engine concepts, and practical experience designing and implementing dimensional models. 
  • Diverse Ingestion Patterns: Proven ability to ingest data from a variety of sources (APIs, SFTP, SQL) and big-data file formats. 
  • Strong Cloud Fundamentals :  A solid understanding of core cloud services, including object storage (ADLS/GCS), secret management (Key Vault/Secret Manager), and compute concepts (VMs, Functions, Containers) 
  • CI/CD for Data: Proven ability to configure and troubleshoot data-specific workflows within a CI/CD framework (GitHub Actions preferred), in partnership with a DevOps team 
  • Communication & Collaboration: Excellent communication skills, with the ability to articulate complex technical concepts to diverse audiences and collaborate effectively with distributed, global teams 

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 64 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  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.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RAGDatabricks

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. Walk me through how you've used Databricks in your day-to-day work.
  3. Describe a typical day in a role like this one: which parts run through AI directly?
  4. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: RAG and Databricks. 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.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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