Data Engineer – Audience Measurement

Ipsos North America

Data Engineer supporting Audience Measurement at Ipsos by developing scalable data pipelines on GCP. Collaborating with engineering leaders and data scientists for optimal data solutions.

Posted 7/8/2026full-timeLondon • 🇬🇧 United KingdomMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

CloudETLGoogle Cloud PlatformPython

About the role

Key responsibilities & impact

Develop robust scalable data pipelines and optimise data storage solutions on GCP.
Implement ETL processes and CI/CD pipelines to ensure clean, structured data ready for use.
Work with data scientists to integrate synthetic models into production environments and provide the guardrails and advice as they develop.
Provide technical support, troubleshoot issues, and research new technologies to enhance capabilities.
Document pipelines and the platform including architectures and user guides, helping to enforce data management standards.
Engage in DataOps practices and improve data delivery performance.
Partner with data scientists on model productionisation. You will establish clear data contracts and shared standards that enable effective collaboration.
Work within an agile framework and participate in agile ceremonies.

Requirements

What you’ll need

Extensive Data Engineering Experience: A proven track record of building robust scalable data pipelines using modern cloud providers (Ideally GCP).
Strong Programming Skills: Expert-level proficiency in Python, with a strong focus on building decoupled, testable functions and clear data contracts.
Serverless & Event-Driven Expertise: Experience with, or strong interest in, decomposing workloads into independent steps orchestrated by managed workflow services and triggered by data events.
Migration & Testing Experience: Experience with safely modernizing legacy systems using parity testing and incremental routing patterns.
IaC & Containerization: Hands-on experience packaging runtimes into portable containers and provisioning cloud resources using modern Infrastructure as Code tools.
Team working / Collaboration: Experience of working with wider teams of Product Managers, Data Scientists, Engineers and non technical staff.

Benefits

Comp & perks

25 days annual leave
pension contribution
income protection
life assurance
health & wellbeing benefits
financial benefits
professional development opportunities
flexibility in working arrangements

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Data Pipeline DevelopmentETL ImplementationCI/CD PipelinesServerless ArchitectureEvent-Driven WorkflowsLegacy System ModernizationTesting and MigrationContainerizationInfrastructure as CodeData Management Standards

Soft Skills

Team CollaborationTechnical SupportProblem Solving