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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, 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.
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.
Your key responsibilities will include:
Vision and Strategy: Champion the architectural vision within your domain. You will translate business needs into a practical, cost-conscious strategy and effectively communicate this to all stakeholders.
Technical Leadership & Line Management: Act as a lead technical authority for data engineering, which includes line management responsibilities for a small team of engineers. You will guide the team on best practices, decoupled logic, and incremental modernization.
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Platform Operations: Oversee the operational health of your team’s data pipelines and systems. You will work 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: Serve as a senior practitioner building event-driven, serverless data pipelines. You will personally implement core architecture, manage cloud project costs, and ensure systems are resilient.
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: Champion agile methodologies. You will collaborate 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. You will explain complex architectural trade-offs to non-technical audiences and ensure the platform meets strategic objectives.
Continuous Improvement: Foster a culture of incremental improvement. You will advocate for safe upgrades using parity testing, avoiding risky rewrites, and ensuring the 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, with a strong focus on building decoupled, testable functions and clear data contracts.
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.
Leadership & Mentorship: Previous line management experience or readiness to step into people leadership and the ability to guide a team of engineers, conduct rigorous code reviews, and author clear architecture decisions.
Cost-Conscious Mindset: A strong understanding of cloud economics, with the ability to design architectures that scale sustainably.
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