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Job details
Hybrid
Office and home days — the ad has the split.
Requirements
Be near London for hybrid days
No relocation package mentioned.
Have senior-level experience
Lead-level role.
Skills
Requirements
What we're looking for
- Demonstrable experience leading technical system designs and defining architecture in a high-scale, cloud-native operational data environment.
- Proven hands-on engineering experience handling high-throughput, real-time data ingestion and processing pipelines.
- Experience mentoring engineers, managing technical debt, and steering code-first DevOps cultures.
Nice to have
- Polyglot Engineering Literacy: Strong backend development capability with a willingness to design, challenge, and review logic across Python and Go, with Java or Scala as valuable secondaries.
- Cloud Native Expertise: Extensive experience with the GCP Stack (GKE, Pub/Sub, BigQuery, Dataflow, Cloud Functions) and event-driven architectures.
- Infrastructure as Code: Deep understanding of automated infrastructure deployment using Terraform and container orchestration via Kubernetes.
- Systems Thinking: Ability to map out complex, multi-project data flows and microservices environments, ensuring modularity and resilience.
- Strategic Communication: Ability to articulate abstract technical designs clearly to both technical engineers and non-technical stakeholders.
- Nice to Have: Familiarity with ESG and/or Sustainable Software Engineering principles to optimise cloud compute efficiency, or experience shifting data capabilities to "Edge" environments.
The role
As a Lead Data Engineer, you operate as a technical orchestrator and a guardian of excellence across our real-time operational data ecosystem. You are positioned at the critical intersection of high-level requirement analysis, distributed systems design, and hands-on delivery.
You will balance deep data architecture with infrastructure architecture, bridging the gap between data pipelines and cloud-native container platforms.
Your time will be balanced across three core pillars:
- 40% High-Level Design & Architecture: Reviewing incoming business requirements, driving technical discussions, and mapping out scalable, distributed data architectures.
- 40% Hands-On Engineering: Writing clean, testable code alongside the team, implementing core platform features, building reusable components and undertaking support requests.
- 20% Mentorship & Technical Governance: Cultivating the engineering squad's capabilities, managing technical debt, and defining quality frameworks.
What you'll do
- Technical Orchestration: Translate complex business roadmaps into high-level designs, defining the structures, components, and interactions of event-driven streaming solutions.
- Data & Infrastructure Architecture: Architect high-throughput, real-time data ingestion pipelines while partnering with DevOps specialists to ensure alignment with cloud infrastructure frameworks.
- People Leadership & Mentoring: Oversee the technical growth and motivation of the engineering squad, running code reviews, sharing knowledge, and embedding engineering best practices.
- Delivery Flow: Partner with the Engineering Manager and Product Managers to refine requirements into technical tasks, ensuring iterative delivery and a lean backlog.
- Operational Excellence & SLA Management: Guard platform reliability against extreme traffic loads, establishing a proactive monitoring strategy via Grafana/Prometheus.
- Escalation & Support: Participate in the team's weekly support rotation as a high-level escalation point, leading Root Cause Analysis when critical operational challenges arise.
How you'll work
Workplace: White City, London - Hybrid 1-2 days a week on site
Contract Type: Permanent
Hiring process
Application
First interview
With a couple of colleagues · 45–60 min
A mix of strengths, technical and scenario questions.
Second interview
With two ITV colleagues
Questions around ITV's behaviours, to get a fuller picture of experience.
Job-specific exercise or task
Not every role
For some roles, a presentation, case study or other practical exercise, either before the interview or on the day.
- Timeline varies depending on application volume and the role.
- Feedback is given after interviews but not after the CV screening stage.
- Application help requests are answered within 2 working days.
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