Pay: Salary not listed in the saved posting
Work setup: Unconfirmed
Employment: Unconfirmed

What you’ll bring

Core experience

Experience: 5+ years of dedicated, hands-on data engineering experience, with a strong track record of delivering production-grade solutions
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.

Qualification wording

Experience: 5+ years of dedicated, hands-on data engineering experience, with a strong track record of delivering production-grade solutions

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.

Tools in this posting

Python
SQL
Databricks
Google Cloud Storage
dbt
Delta

Source

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.

- 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.

- 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.

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.

- 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.

- 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.

- 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)

- 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.

- 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

- 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.

Job description

View original posting ↗

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.

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Source & posting history

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Source excerpts

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Pay: No pay amount identified in the saved description.
Location & working pattern: Chennai, India
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.
Work authorization: No clear work-authorization passage found. Eligibility is unconfirmed.

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