Analytics Engineer

Analytics Engineer

Full-Time 36000 - 60000 £ / year (est.) No home office possible
IAG Loyalty

At a Glance

  • Tasks: Build and evolve digital data models to enhance customer experiences.
  • Company: Join IAG Loyalty, a leader in travel and experiences.
  • Benefits: Flexible hybrid working, competitive salary, and a focus on personal growth.
  • Other info: Dynamic team environment with opportunities for continuous learning.
  • Why this job: Shape the future of digital analytics and make a real impact.
  • Qualifications: Experience with digital product data and strong SQL skills required.

The predicted salary is between 36000 - 60000 £ per year.

We’re IAG Loyalty - one organisation with two ambitious, growing divisions across Loyalty and Holidays. Each has its own goals, strategy and team, but together we’re united by a shared vision to create a more rewarding world of travel and experiences. Our Loyalty division is home to Avios, the global loyalty currency, enabling millions of members to collect and spend rewards across travel, retail and financial services. Our Holidays division including British Airways Holidays and Iberia Vacaciones, brings together trusted brands, connecting customers to thousands of destinations worldwide through seamless, end-to-end travel experiences. We’re on an exciting journey of growth and transformation – we’re going places.

As an Analytics Engineer in the Loyalty division, you’ll play a central role in how we understand digital behaviour across Avios.com and the Avios app. You won’t just be moving data from A to B, you’ll be shaping how we model it, how we trust it, and how we use it to improve our digital experiences. From browsing to checkout, from feature launch to experimentation, you’ll help connect what customers do online to real commercial outcomes. You’ll work with web and app interaction data and turn it into trusted, reusable datasets that power insight across the division. You’ll partner closely with analysts, implementation engineers and data engineers to make sure tracking is clean, structured and ready to unlock value. This is a hands-on role with genuine autonomy. You’ll have the space to decide how things are built, improve what exists, and introduce better ways of working. As our experimentation capability evolves, you’ll help shape the data foundations that sit behind it. If you’re excited by the idea of building something that’s still maturing, where you can create, test, learn and continuously improve, this is that opportunity.

What you’ll be doing

  • Build and evolve digital data models that turn raw web and app interaction data into reliable, analysis-ready datasets people trust.
  • Create well-structured, reusable datasets that enable self-serve reporting and faster decision-making across the business.
  • Partner with analysts to explore customer journeys and digital behaviour, helping uncover opportunities to optimise experiences and improve conversion.
  • Help design and improve how we measure experiments, building models that can act as a clear source of truth.
  • Connect digital interaction data with commercial and campaign performance data to give a more complete view of the end-to-end journey.
  • Contribute to best practices in data quality, documentation and testing, while keeping things pragmatic and focused on progress over perfection.

You’ll have real ownership here. Not just delivering tickets but influencing how our analytics engineering capability develops over time.

What we need from you

We’re looking for someone who enjoys working at the intersection of digital analytics and data engineering and wants to keep growing in that space. You’ll bring:

  • Strong experience working with digital product data (web and/or app), and a solid understanding of event tracking and customer journeys.
  • Advanced SQL skills.
  • Experience working with digital analytics and tracking tools (e.g. GA, Adobe), and an understanding of how tracking decisions impact downstream data.
  • Confidence transforming raw event data into something structured, trusted and genuinely useful for stakeholders.
  • A commercial mindset: you’re curious about conversion, attribution and how digital behaviour links to revenue and performance.
  • A collaborative approach: you enjoy working with analysts, engineers and product teams to solve problems together.
  • A desire to keep learning. Whether you’re strengthening your analytics engineering capability or building deeper technical skills (e.g. Python), you’re motivated to grow through hands-on delivery.

Most importantly, you’re comfortable with autonomy. You like owning your space, shaping solutions, and improving things as you go.

We might not be right for you if:

  • You only want to focus on your to-do list; we’re a small, high-performing team, we help each other to succeed.
  • You value perfection over fast iteration and progress; IAG Loyalty moves fast, we learn and iterate as we go; our environment isn’t right for everyone.

If you think you have what it takes but don't meet every single point above, please do still apply. We’d love to chat and see if you could be a great fit.

The Blend

This role will work as part of our Loyalty Division and is based out of our London office. We call our approach to hybrid working The Blend — it’s about giving you the flexibility to choose where you do your best work, while staying connected with your team and the wider business. This means you will be required to spend at least two days per week in the office, with the rest of the time working from home. You may also be required to work from one of our other office or partner locations, based on your role and 'to do' list.

Diversity and Inclusion

Our vision is to create a more rewarding world of travel and experiences. Delivering that requires diverse thinking and inclusive leadership. We are committed to building a workplace where people feel they belong and are valued for their perspective. Inclusion drives better decisions, stronger performance and more innovative outcomes. We actively encourage applications from people with different experiences and backgrounds, and are committed to ensuring our recruitment process is fair, inclusive and accessible.

Analytics Engineer employer: IAG Loyalty

IAG Loyalty is an exceptional employer, offering a dynamic work environment in London where innovation and collaboration thrive. As an Analytics Engineer, you'll enjoy the autonomy to shape data solutions while being part of a supportive team that values diverse perspectives and continuous learning. With flexible hybrid working arrangements and a commitment to employee growth, IAG Loyalty provides a rewarding opportunity to contribute to the evolution of digital experiences in the travel industry.
IAG Loyalty

Contact Detail:

IAG Loyalty Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Analytics Engineer

✨Tip Number 1

Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.

✨Tip Number 2

Show off your skills! Create a portfolio or GitHub repository showcasing your projects and analytics work. This gives you a chance to demonstrate your expertise and creativity beyond just a CV.

✨Tip Number 3

Prepare for interviews by practising common questions and scenarios related to analytics engineering. Think about how you can articulate your experience with digital product data and event tracking in a way that highlights your problem-solving skills.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at IAG Loyalty.

We think you need these skills to ace Analytics Engineer

Digital Product Data Analysis
Event Tracking
Customer Journey Mapping
Advanced SQL
Digital Analytics Tools (e.g. GA, Adobe)
Data Transformation
Commercial Mindset
Collaboration
Python
Data Quality Best Practices
Documentation
Testing
Autonomy
Problem-Solving

Some tips for your application 🫡

Tailor Your Application: Make sure to customise your CV and cover letter for the Analytics Engineer role. Highlight your experience with digital product data and event tracking, as this will show us you understand what we're looking for.

Showcase Your Skills: Don’t just list your skills; demonstrate them! Use specific examples of how you've used SQL or digital analytics tools in past projects. This helps us see your practical experience in action.

Be Authentic: We want to know the real you! Share your passion for analytics and your desire to learn and grow. If you’ve got a unique perspective or experience, let it shine through in your application.

Apply Through Our Website: For the best chance of getting noticed, apply directly through our website. It’s the easiest way for us to keep track of your application and ensures you’re considered for the role!

How to prepare for a job interview at IAG Loyalty

✨Know Your Data Models

As an Analytics Engineer, you'll be working with digital data models. Make sure you understand how to build and evolve these models. Brush up on your SQL skills and be ready to discuss how you've transformed raw data into reliable datasets in your previous roles.

✨Showcase Your Collaboration Skills

This role requires a collaborative approach, so be prepared to share examples of how you've worked with analysts, engineers, and product teams. Highlight any projects where teamwork led to successful outcomes, especially in optimising customer journeys or improving conversion rates.

✨Demonstrate Your Commercial Mindset

The company values a commercial mindset, so think about how you can connect digital behaviour to revenue. Be ready to discuss your understanding of conversion and attribution, and how your analytical insights have driven business performance in the past.

✨Embrace Autonomy and Iteration

This position offers genuine autonomy, so show that you're comfortable taking ownership of your work. Share experiences where you've shaped solutions and improved processes, and emphasise your ability to learn quickly and iterate based on feedback.

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