Data Engineer - Audience Measurement

As a Data Engineer, you will work in the team to guide the platform's evolution toward serverless, event-driven patterns, moving away from container-orchestrated workflows toward managed cloud services.

Platform Operations:

• 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.

Data Science & Analytics Enablement: Partner with data scientists on model productionisation. You will establish clear data contracts and shared standards that enable effective collaboration.

Agile Delivery: Work within an agile framework. Participate in agile ceremonies and provide occasional client interaction.

Team Working / Stakeholder Engagement: Provide technical advice and guidance for internal teams and occasionally clients. Explain complex technical solutions to non-technical audiences.

Continuous Improvement: Foster a culture of incremental improvement.

Vision and Strategy: Support the architectural as set out by the Lead Data Engineer.

To be successful in this role, your technical skills should be matched by a pragmatic approach.

• 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.

Pulled from the full job description

• Annual leave
• Company pension, We offer a comprehensive benefits package designed to support you as an individual. Our standard benefits include 25 days annual leave, pension contribution, income protection and life assurance. In addition, there are a range of health & wellbeing, financial benefits and professional development opportunities.

We realise you may have commitments outside of work and will consider flexible working applications - please highlight what you are looking for when you make your application. We have a hybrid approach to work and ask people to be in the office or with clients for 3 days per week.

We are committed to equality, treating people fairly, promoting a positive and inclusive working environment and ensuring we have diversity of people and views. We recognise that this is important for our business success - a more diverse workforce will enable us to better reflect and understand the world we research and ultimately deliver better research and insight to our clients. We are proud to be a member of the Disability Confident scheme, certified as Level 2 Disability Confident Employer. We are dedicated to providing an inclusive and accessible recruitment process.

Ipsos is recruiting a Data Engineer to help drive the technical evolution of our Audience Measurement data platforms. Joining a wider group of engineering leaders, you will work as part of a team championing an architecture rooted in managed cloud services, cost-conscious design, and incremental improvement. You will work closely with internal teams to Develop robust scalable data pipelines and optimise data storage solutions on GCP. What is in it for you? This is a fantastic opportunity for a mid-career / level person to work on technologies chosen intentionally, favouring proven tools that reduce cognitive load and maximise team velocity. Our core ecosystem revolves around: * Modern Python for backend services and data processing. * Cloud-native serverless compute and managed workflow orchestrators. We operate across both AWS and GCP. Deep expertise in either is welcome, with opportunities to cross-train on the other. * Serverless NoSQL, Object Storage, and Serverless Analytics for our data layers. * Event buses and messaging queues for asynchronous, decoupled processing. * Infrastructure as Code (Pulumi/Terraform) and containerized deployments.