Lead Data Engineer: Audience Measurement Platform

Ipsos in the UK; Cambridge; Hybrid; GBP 90,000 - 120,000; Full time

Benefits offered by this job

25 days annual leave

Pension contribution

Income protection

Life assurance

Health & wellbeing

Financial benefits

Professional development opportunities

Job summary

Ipsos in the UK is recruiting a Lead Data Engineer to advance our Audience Measurement data platforms. You will guide architecture, own data pipelines, and collaborate with Product Managers to deliver scalable, cost-conscious solutions.

You’ll lead a small team, apply serverless patterns, and partner with data scientists to productionise models. A hybrid working approach is available with strong emphasis on observable, well-documented systems.

Qualifications

• Extensive data platform design and build experience on modern cloud providers (AWS or GCP).
• Strong Python expertise for backend services and data pipelines.
• Experience with serverless architectures and managed workflows.

Responsibilities

• Define and communicate architectural vision for the data platform.
• Provide technical leadership and line management for a small team.
• Oversee platform operations, observability, and IaC/containers.
• Hands-on engineering to implement event-driven, serverless pipelines.
• Partner with data scientists for model productionisation and data contracts.
• Champion agile delivery with product managers for iterative capability delivery.
• Engage with clients and internal teams to explain architecture and decisions.
• Drive continuous improvement and safe upgrade strategies.

Skills

Python

Data engineering

Cloud (AWS/GCP)

Serverless

IaC

Leadership

Tools

Pulumi/Terraform

Containerization

Job description

Ipsos in the UK is recruiting a Lead Data Engineer to advance our Audience Measurement data platforms. You will guide architecture, own data pipelines, and collaborate with Product Managers to deliver scalable, cost-conscious solutions.

You’ll lead a small team, apply serverless patterns, and partner with data scientists to productionise models. A hybrid working approach is available with strong emphasis on observable, well-documented systems.