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 operationa
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