Who We Are

VML is a global creative company that combines brand experience, customer experience, and commerce to create connected brands that drive growth. Guided by a Human First philosophy, VML is known for its innovative work for brands and consistently ranks among the world’s leading creative companies, including the WARC Creative 100. VML’s global network spans 55+ markets with principal offices in Buenos Aires, Kansas City, London, New York, São Paulo, Shanghai and Singapore.

VML is part of WPP, the trusted growth partner for the world's leading brands. Powered by exceptional talent and our agentic marketing platform WPP Open, WPP unites cutting-edge media intelligence and data solutions, creativity, production, enterprise solutions and expert strategic counsel.

For more information, please visit www.vml.com and follow along on LinkedIn #WeAreVML.

We are looking for a Senior Data Engineer to join VML and play a key role in designing, developing, and evolving scalable enterprise data solutions.

In this role, you will work across data engineering, architecture, analytics, automation, and AI initiatives, helping transform complex data from multiple sources into reliable, secure, and scalable solutions.

You will collaborate with global and regional teams across Data, Business Intelligence, Marketing, Sales, Technology, and Leadership, translating business needs into robust technical solutions while contributing to the modernization of our data ecosystem.

What You'll Do

Design, develop, and optimize scalable enterprise data solutions and architectures.
Build and maintain end-to-end data pipelines, including data ingestion, transformation, processing, and integration.
Design and implement solutions using Microsoft Fabric, including Lakehouses, Warehouses, OneLake, Dataflows Gen2, Pipelines, and Notebooks.
Develop and optimize complex SQL queries, stored procedures, tables, views, and database processes.
Design and maintain Data Warehouses, Data Lakes, dimensional models, and semantic layers.
Integrate data from multiple enterprise sources, including CRM systems, marketing automation platforms, Adobe Analytics, operational systems, and APIs.
Automate data transformation and validation processes using Python, PowerShell, or similar technologies.
Implement data quality processes to ensure accuracy, consistency, reliability, and traceability.
Contribute to data governance, security, compliance, and enterprise data standards.
Support the development of AI-driven and agentic solutions, enabling trusted data foundations for automation and advanced analytics.
Drive continuous improvement through automation, scalability, and the adoption of emerging technologies.
Lead complex data initiatives, managing priorities, dependencies, risks, and technical delivery.
Collaborate with technical and business stakeholders to translate requirements into scalable data solutions.
Establish and promote engineering best practices across data development, automation, and architecture.
Mentor and provide technical guidance to junior and mid-level team members.

What We're Looking For

5+ years of experience in Data Engineering, Data Analytics, Business Intelligence, Enterprise Analytics, or related roles.
Strong hands-on experience with Microsoft Fabric, Azure, SQL Server, Power BI, and enterprise data platforms.
Advanced SQL skills, including query optimization, performance tuning, stored procedures, and indexing strategies.
Strong experience with ETL/ELT processes, data pipelines, and workflow orchestration.
Experience designing and optimizing Data Warehouses, Data Lakes, dimensional models, and scalable data architectures.
Experience integrating multiple enterprise data sources and APIs.
Experience with Python, PowerShell, or similar scripting technologies.
Knowledge of data governance, security, compliance, and data quality principles.
Understanding of Microsoft Entra ID, RBAC, managed identities, data classification, DLP, and enterprise data security is a plus.
Exposure to AI, Copilot, agentic AI, intelligent automation, predictive analytics, or machine learning is highly valued.