Head of Data Engineering

London
9 months ago
Applications closed

Related Jobs

View all jobs

Associate Director, AI & Advanced Analytics

Head of Data Engineering

Are you ready to shape the future of digital advertising through data? A fast-growing, innovative ad tech company is looking for a Head of Data Engineering to lead the development of its audience intelligence and targeting infrastructure. This is a rare opportunity to build from the ground up and make a direct impact on campaign performance for some of the world's most recognisable brands.

What You'll Do

As Head of Data Engineering, you'll sit at the intersection of data, strategy, and technology. Your mission: to design and manage the systems that power audience targeting across a video advertising platform.

Key Responsibilities:

Audience Data Infrastructure: Build and evolve the architecture for ingesting, storing, and activating digital audiences across publisher and SSP networks.
Data Pipelines: Design robust pipelines to process real-time and historical data for audience segmentation.
Identity Resolution: Lead the integration of identity resolution solutions to unify first- and third-party data sources.
AI/ML Integration: Apply machine learning models to enhance audience classification and predictive targeting.
Cross-Functional Collaboration: Partner with AdOps, Sales, and Strategy teams to align data capabilities with campaign goals.
Innovation: Drive the shift from cookie-based targeting to contextual and outcome-driven models.What You'll Bring

5+ years in data engineering or programmatic media, ideally within ad tech, SSPs, or media agencies.
Proven experience with identity resolution and customer data integration (e.g., LiveRamp, Adobe, or custom solutions).
Strong programming skills in Python or similar languages.
Deep understanding of programmatic advertising ecosystems and privacy regulations (e.g., GDPR).
Experience applying ML/AI for segmentation or targeting.
Excellent communication skillsWe Are Aspire Ltd are a Commited employer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise AI Jobs in the UK (2026 Guide)

Advertising AI jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly informed and in demand across multiple sectors simultaneously. General job boards reach a broad audience but lack the specificity that AI professionals expect — and the filtering mechanisms they rely on. Specialist platforms, direct outreach and academic channels each serve a different part of the market. This guide, published by ArtificialIntelligenceJobs.co.uk, covers where to advertise AI roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about time-to-hire across different role types.

New AI Employers to Watch in 2026: UK and Global Companies Reshaping AI Careers

The artificial intelligence job market in the UK is evolving at an extraordinary pace. With record-breaking investment, government backing, and a surge in enterprise adoption, the landscape of AI employers is shifting rapidly. For candidates exploring opportunities on ArtificialIntelligenceJobs.co.uk, understanding who is hiring next is just as important as understanding what skills are in demand. In this article, we explore the new and emerging AI employers to watch in 2026, focusing on organisations that have recently secured funding, won major contracts, or expanded their UK footprint. From cutting-edge startups to global giants doubling down on Britain, these companies represent the next wave of AI career opportunities.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.