Senior Data Engineer - Audience Measurement

Lead Data Engineer - Audience Measurement

Ipsos is recruiting a Lead Data Engineer to help drive the technical evolution of our Audience Measurement data platforms. Joining a wider group of engineering leaders, you will act as a technical anchor for your team championing an architecture rooted in managed cloud services, cost‑conscious design, and incremental improvement. You will work closely with Product Managers to define requirements and our Production team to ensure operational stability, delivering scalable and modern data solutions.

This is a fantastic opportunity to work on technologies chosen intentionally, favoring proven tools that reduce cognitive load and maximize 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 No
  
  SQL, 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.

As a Lead Data Engineer, you will guide the platform’s evolution toward serverless, event‑driven patterns, moving away from container‑orchestrated workflows toward managed cloud services.

• Vision and strategy: champion the architectural vision within your domain, translating business needs into a practical, cost‑conscious strategy and effectively communicating it to all stakeholders.
• Technical leadership & line management: act as a lead technical authority for data engineering, including line‑management responsibilities for a small team of engineers. Guide the team on best practices, decoupled logic, and incremental modernization.
• Platform operations: oversee the operational health of your team’s data pipelines and systems, working closely with our Production team to ensure systems are highly observable, well‑documented, and easy to operate via Infrastructure as Code and containerization.
• Hands‑on engineering: personally implement core architecture, manage cloud project costs, and ensure systems are resilient.
• Data science & analytics enablement: partner with data scientists on model productionisation, establishing clear data contracts and shared standards that enable effective collaboration.
• Agile delivery: champion agile methodologies, collaborating closely with Product Managers to ensure clear requirements and drive the continual, iterative delivery of new capabilities.
• Stakeholder and client relations: act as a key technical advisor for clients and internal teams, explaining complex architectural trade‑offs to non‑technical audiences and ensuring the platform meets strategic objectives.
• Continuous improvement: foster a culture of incremental improvement, advocating for safe upgrades using parity testing, avoiding risky rewrites, and ensuring long‑term maintainability of the codebase.

To be successful in this role, your technical skills should be matched by a pragmatic, cost‑first approach to problem‑solving.

• Extensive data engineering experience: a proven track record of designing, building, and maintaining scalable data platforms using modern cloud providers (AWS or GCP).
• 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.
• Strong programming skills: expert‑level proficiency in Python, focusing on building decoupled, testable functions and clear data contracts.
• Migration & testing…