Head of Data Engineering

MAG (Airports Group)
Manchester
1 month ago
Applications closed

Related Jobs

View all jobs

Head of Data Engineering - London

Head of Data Engineering

Head of Data Engineering

Head of Data Engineering

Head of Data Engineering

Head of Data Engineering

Select how often (in days) to receive an alert:


For airports, for partners, for people. We are CAVU.


At CAVU, our purpose is to find new and better ways to make airport travel seamless and enjoyable for everybody—from the smallest ideas to the biggest transformations. Every day is an opportunity to create better travel experiences.


From our revenue-accelerating single-platform technology, Propel, through to our world-class hospitality venues including 1903 and Escape Lounges, our solutions make travel smoother for passengers and more profitable for our clients and partners.


We know that to bring your best ideas, you need the space to think, the support to grow, and the freedom to be your authentic self. Whether you’re working from our offices, from home, in our lounges, or on the road, we provide an environment where you can create, innovate, and help transform airport travel.


If you’re looking for a career where you can make a real impact, bring new ideas to life, and push boundaries, then CAVU is the place for you.


Together, we can reach new heights. Together, we are CAVU.


What’s the role?

CAVU is well into an exciting digital and data transformation journey. With the acquisition of new brands, the expansion of our product portfolio, and a commitment to best-in-class technology, data has become fundamental to how we operate and grow.


As we progress towards a fully event-based architecture with data quality at the heart of everything we do, we’re now looking for a Head of Data Engineering to join our Data leadership team.


This role will shape, strengthen, and scale our centralised data engineering function—ensuring our platforms, pipelines, and architecture are robust, forward-thinking, and fit for the future. You’ll bring deep expertise across modern data engineering practices, strong technical solution-design capability (particularly with Databricks), and the leadership to empower a high-performing engineering team.


Key Responsibilities

  • Team Leadership: Lead, manage and mentor a team of data engineers, fostering a culture of collaboration, learning, and innovation.
  • Strategic Ownership: Develop and execute the data engineering strategy, ensuring alignment with business objectives and long-term data ambitions.
  • Data Architecture: Design, oversee, and continually improve CAVU’s data storage, processing, and integration architecture.
  • Pipeline Excellence: Ensure the delivery of scalable, high-quality data pipelines for ingestion, transformation and storage.
  • Cross-Functional Collaboration: Partner closely with data science, analytics, product, and engineering teams to ensure data is accessible, discoverable, and meets CAVU standards.
  • Data Quality & Governance: Establish and champion best practices for data quality, governance, observability, and security.
  • Technology Evaluation: Stay ahead of data engineering trends and evaluate emerging tools to enhance the team’s capabilities.
  • Budget & Resource Management: Own the data engineering budget and ensure efficient use of infrastructure and resources.
  • Stakeholder Management: Anticipate issues, remove blockers, and communicate effectively with technical and non-technical stakeholders.

About You

You’re a strategic and hands-on data leader with a passion for building scalable systems, high-performing teams, and exceptional data products. You’re motivated by solving complex problems, enabling others to thrive, and shaping the future of data at CAVU.


Qualifications & Experience

  • Strong experience with medallion architecture and Databricks
  • Proficiency with ETL tools (e.g., Rivery) and ML-Ops frameworks
  • Strong programming skills (Python, Scala or Java)
  • Experience with cloud platforms (AWS, Azure, or GCP)
  • Excellent communication skills with the ability to bring clarity to complexity
  • Proven ability to anticipate problems and resolve them with ease

Preferred

  • Experience working in a SaaS environment
  • Exposure to machine learning and AI tooling

The Perks

  • 25 days holiday, increasing with service (up to 28)
  • Option to buy up to 10 extra days + 4 flexible bank holidays
  • 10% company pension
  • On-site gym
  • A range of flexible benefits and discounts, including up to 50% off CAVU products such as Escape Lounges and Airport Parking
  • Rail and retail discounts
  • 2 paid volunteering days per year
  • Access to health & wellbeing events, ID&E activities, and learning opportunities
  • Formal and informal development options, including mentoring programmes and learning grants
  • Enhanced parental leave (T&Cs apply)

The Interview Process

  • Recruiter Screen (approx. 15 minutes) – We’ll cover your experience, motivations, and role fit
  • Skills & Competency Interview
  • Values Interview

Equal Opportunities & Reasonable Adjustments

We’re building something brilliant at CAVU: a diverse team of People who reflect the global customer base that we serve. We’re proudly part of MAG and together we’re on a mission to be number one in our industries, and that takes talent in all its forms. With so many exciting roles across businesses, there’s space of your unique strengths to shine.


Whether this is your first role or your next big step, we want to hear from you – even if you don’t think you tick every box. What matters most is what you bring.


We’re proud to be a Disability Confident employer. If you need any adjustments to support your application or interview, just let us know. We’re committed to helping you perform at your best.


At MAG and CAVU, every journey matters. Our Colleague Communities play a big part in that: Women’s Network, Embrace (Race & Ethnicity), Fly with Pride (LGBTQIA+), Mind Matters (Mental Health), PACT (Parents & Carers), RespectABILITY (Disability & Neurodiversity), and the CAVU Global ID&E Affinity Group.


#J-18808-Ljbffr

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.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.