Senior Data Engineer

Burson part of WPP is the global communications leader built to create value for clients through reputation. With highly specialized teams industry-leading technologies and breakthrough creative we help brands and businesses redefine reputation as a competitive advantage so they can lead today and into the future. When you work at Burson you are part of a global community of lifelong learners who thrive at the edge of innovation.

WPP (LSE/NYSE: WPP) is the trusted growth partner for the worlds leading brands. We unitecutting-edge media intelligence and data solutions world-class creativity next-generation production transformative enterprise solutions and expert strategic counselin a single company powered by exceptional talent and our agentic marketing platform WPP Opento help our clients navigate change capture opportunity and deliver transformational growth. For more information visit

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More about the role:

Bursons Intelligence & Insights capability builds the data infrastructure pipelines and AI-enabled workflows that power communications measurement and impact reporting at scale. Reporting directly to JT Joseph within the Intelligence & Insights practice and based in London UK (Hybrid working policy) this role is central to leading the technical development of Fount Bursons flagship communications intelligence platform.

In this role you will be responsible for translating product vision and technical specifications into robust scalable data engineering and business intelligence solutions. Working closely with product leadership you will contribute technical insights and architectural recommendations that help shape the platforms future evolution. You will operate within a structured Agile team managed in Jira where product vision priorities and roadmaps are set by Product Owners while your core focus is executing this vision to the highest engineering standards.

You will serve as the lead engineer responsible for building maintaining and enhancing Fount Bursons custom data pipeline and database layer for communications reporting. Fount enables analysts to configure client monitoring subscriptions Boolean searches data ingestion and AI enrichment through an analyst-facing configuration layer. Under the direction of product leadership you will execute technical deliverables that make the platform more reliable scalable and seamless for non-technical users to configure and operate.

This is a senior individual-contributor role with technical leadership and mentoring responsibility rather than a formal people-management position. You will directly mentor a junior engineer while providing technical peer support and alignment across the wider engineering team. The position combines strategic engineering with hands-on delivery across major pillars:

• Technical Leadership & Architecture (e.g. pipeline design engineering standards technical reviews technical debt refactoring mentoring)
• Fount Platform & Data Engineering (e.g. ETL/ELT pipelines Python services SQL layers API integrations cloud infrastructure cost & performance optimization)
• Analyst Enablement & AI Integrations (e.g. NocoDB configuration Boolean ingestion LLM enrichment frameworks MCP & provider-hosted integrations)

What youll do:

• Lead the technical design architectural standards and delivery of business-critical data pipelines services and platform components across media monitoring and communications data sources.
• Partner closely with Product Owners in an Agile Jira environment to assess technical feasibility evaluate trade-offs and translate product requirements into maintainable scalable technical solutions.
• Build and maintain production-ready Python services SQL transformation layers star-schema data models and API integrations across relational databases and cloud storage (Azure Data Lake).
• Optimise pipeline performance system reliability compute efficiency and AI token costs while establishing robust monitoring logging alerting and incident-response practices.
• Enhance Founts analyst-facing configuration layer (Boolean searches API ingestion rules NocoDB workflows) to streamline analyst setup and reduce routine engineering intervention.
• Operationalise AI-enabled enrichment frameworks (classification summarisation sentiment topic detection LLMs MCP-enabled integrations) with strict quality assurance governance and cost controls.
• Deliver custom data engineering solutions for specialized client requirements integrating internal API-driven and third-party research datasets into scalable reporting workflows.
• Mentor junior engineers through code reviews pairing architectural guidance and knowledge-sharing while systematically refactoring technical debt and maintaining operational runbooks.

Experience that contributes to success:

• Substantial experience designing building and operating production data platforms star-schema data models and complex ELT/ETL pipelines.
• Advanced proficiency in Python and SQL including clean object-oriented design Pandas query optimization and REST API integrations.
• Hands-on experience within the Microsoft Azure ecosystem (Azure Data Factory Azure SQL ADLS) Azure DevOps Git CI/CD pipelines and automated testing.
• Proven track record in system reliability engineering production troubleshooting logging/monitoring and performance optimization.
• Demonstrated capability mentoring junior engineers and elevating team capabilities through code reviews technical standards and documentation.
• Agile execution expertise using Jira partnering closely with Product Owners to evaluate technical trade-offs and manage competing roadmap priorities.
• Familiarity with modern AI & integration frameworks including LLM enrichment workflows semi-structured formats (e.g. Parquet) NoSQL and provider-hosted or MCP-enabled integrations.
• Exposure to complementary technologies such as low-code UI tools (NocoDB/Airtable) Infrastructure as Code (Terraform/Terragrunt) Power BI/DAX or communications measurement data.

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