Senior Data Engineer - Global People Data

Why we're hiring:

WPP is at the forefront of the marketing and advertising industry's largest transformation. Our Global CIO is leading a significant evolution of our Enterprise Technology capabilities, bringing together over 2,500 technology professionals into an integrated global team. This team will play a crucial role in enabling the ongoing transformation of our agencies and functions. 

We are seeking a Senior Data Engineer to serve as the technical anchor for WPP's global people data product. This is a hands-on senior role within the People Data & Insights team, responsible for the design, implementation, and ongoing evolution of the data pipelines and models that underpin enterprise-wide workforce reporting, regulatory compliance, and strategic people analytics across 90+ markets and 100K+ employees. 

This is not a coordination role. It requires deep, practised data engineering capability combined with the architectural judgement to make enterprise-grade design decisions independently — with full autonomy over schema, ingestion patterns, data standardisation, and pipeline architecture — in a complex, multi-source, globally scaled environment. 

What you'll be doing:

• Pipeline Design & Delivery: Lead the design and implementation of core data pipelines that ingest, transform, and model people data from multiple HR and workforce systems — including Workday — into a governed, enterprise-grade data model built on Databricks and Delta Lake. 
• Data Modelling & Standards: Own and evolve canonical people data structures across the global people data platform. Define and enforce schemas, ingestion patterns, and transformation logic that support scalability, consistency, and downstream reporting, analytics, and regulatory use cases. 
• Technical Decision Authority: Make day-to-day architectural and design decisions independently — on schema design, data standardisation approaches, and pipeline patterns — reducing escalation to senior leadership and enabling faster, higher-confidence delivery. 
• Regulatory & Compliance Enablement: Ensure pipelines and data models are designed and maintained to support statutory requirements, including the EU Pay Transparency Directive, UK Gender Pay Gap reporting, and ESG/CSRD workforce data obligations. 
• Platform Alignment: Partner closely with enterprise data and business platforms teams to ensure the people data architecture aligns with WPP's broader data platform standards, governance frameworks, and integration patterns. 
• Technical Leadership: Provide senior technical guidance, code review, and architectural oversight to other data engineers within the team — raising standards, improving consistency, and building engineering capability across the function. 
• Governance & Quality: Embed data quality checks, validation frameworks, and governance controls into pipeline and model design — ensuring the platform remains accurate, audit-ready, and defensible for executive and regulatory reporting. 

What you'll need:

• Hands-on data engineering experience, including design and delivery of complex pipelines and data models in a cloud environment 
• Strong proficiency in SQL; solid Python and/or PySpark capability
• Demonstrable experience with Databricks, Apache Spark, and Delta Lake architecture
• Proven ability to design and own enterprise-grade canonical data models across multiple upstream source systems
• Experience integrating data from APIs and diverse upstream platforms at scale
• Azure cloud platform experience
• Strong data governance and quality mindset — experience building validation, reconciliation, and audit frameworks into pipeline design
• Able to make independent technical design decisions and operate with a high degree of autonomy in a lean, fast-moving team
• Experience providing technical guidance or oversight to other engineers
• Familiarity with HR, people, or workforce data systems (e.g., Workday, BambooHR, HiBob, Greenhouse)
• Experience with regulatory or compliance-driven data requirements (e.g., EU Pay Transparency, GDPR, ESG/CSRD)
• Experience designing multi-layer data architectures (raw → enriched → curated) for downstream analytics and reporting consumption
• Understanding of data product thinking — building governed data assets for use by analytics, reporting, and executive audiences
• Experience working in a federated, globally distributed organisation with complex source system landscapes 

Who you are: