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- Tasks: Lead the development of audience intelligence and targeting infrastructure in digital advertising.
- Company: Join a fast-growing, innovative ad tech company making waves in digital advertising.
- Benefits: Enjoy a dynamic work environment with opportunities for innovation and impact.
- Why this job: Shape the future of advertising while collaborating with top brands and teams.
- Qualifications: 5+ years in data engineering, strong programming skills, and experience with identity resolution.
- Other info: We are a Disability Confident Committed employer.
The predicted salary is between 43200 - 72000 £ per year.
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 skills
We Are Aspire Ltd are a Disability Confident Commited employer #J-18808-Ljbffr
Head of Data Engineering (London) employer: We Are Aspire
Contact Detail:
We Are Aspire Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of Data Engineering (London)
✨Tip Number 1
Network with professionals in the ad tech industry, especially those who have experience in data engineering. Attend relevant meetups or conferences to connect with potential colleagues and learn about the latest trends in audience targeting and data infrastructure.
✨Tip Number 2
Showcase your technical skills by contributing to open-source projects or creating your own data engineering projects. This will not only enhance your portfolio but also demonstrate your hands-on experience with programming languages like Python and your understanding of data pipelines.
✨Tip Number 3
Familiarise yourself with the latest advancements in AI and machine learning as they relate to audience segmentation and targeting. Being able to discuss these topics intelligently during interviews can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss your experience with identity resolution and customer data integration solutions. Be ready to provide examples of how you've successfully implemented these technologies in past roles, as this is a key requirement for the Head of Data Engineering position.
We think you need these skills to ace Head of Data Engineering (London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly within ad tech or similar fields. Emphasise your skills in Python and any experience with identity resolution and customer data integration.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data and digital advertising. Discuss how your background aligns with the responsibilities of the Head of Data Engineering role and mention specific projects where you've successfully implemented data solutions.
Showcase Your Technical Skills: Include specific examples of your programming skills and any machine learning models you've applied. Highlight your understanding of programmatic advertising ecosystems and privacy regulations, as these are crucial for the role.
Prepare for Potential Questions: Think about how you would approach the key responsibilities listed in the job description. Be ready to discuss your strategies for building audience data infrastructure and integrating AI/ML into targeting solutions during an interview.
How to prepare for a job interview at We Are Aspire
✨Showcase Your Technical Expertise
As a Head of Data Engineering, you'll need to demonstrate your strong programming skills, particularly in Python or similar languages. Be prepared to discuss specific projects where you've designed data pipelines or integrated identity resolution solutions.
✨Understand the Ad Tech Landscape
Familiarise yourself with the programmatic advertising ecosystem and privacy regulations like GDPR. During the interview, highlight your experience in these areas and how it can benefit the company's audience targeting strategies.
✨Emphasise Cross-Functional Collaboration
This role requires working closely with various teams such as AdOps and Sales. Share examples of how you've successfully collaborated across departments in the past to align data capabilities with campaign goals.
✨Demonstrate Innovation and Adaptability
The company is looking for someone who can drive innovation in audience targeting. Be ready to discuss your ideas on shifting from cookie-based targeting to more contextual and outcome-driven models, showcasing your forward-thinking approach.
