At a Glance
- Tasks: Lead the design and engineering of real-time data systems while mentoring a talented team.
- Company: Join ITV, a leading media company with a focus on innovation and collaboration.
- Benefits: Enjoy a competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Be part of a forward-thinking team that values sustainability and technical excellence.
- Why this job: Make a significant impact in a dynamic environment while working with cutting-edge technologies.
- Qualifications: Experience in backend development, cloud-native architectures, and mentoring engineers.
The predicted salary is between 63000 - 77000 £ per year.
Workplace: White City, London – Hybrid 1-2 days a week on site
Contract Type: Permanent
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.
Key Responsibilities
- 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.
What You’ll Bring
- 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.
Minimum Criteria
- 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.
Lead Data Engineer ITV Careers employer: Deaf Unity
Deaf Unity is an exceptional employer that fosters a collaborative and inclusive work culture in the vibrant city of Leeds. With a strong commitment to employee growth, we offer numerous professional development opportunities and encourage innovative thinking to drive business success. Join us to be part of a meaningful mission that not only impacts the media landscape but also champions diversity and inclusion within the industry.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer ITV Careers
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Lead Data Engineer ITV Careers
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Deaf Unity. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Deaf Unity
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
