At a Glance
- Tasks: Transform complex data into actionable insights to enhance aircraft availability and operational performance.
- Company: Join easyJet, a leading low-cost airline connecting millions across Europe.
- Benefits: Enjoy a competitive salary, bonus, flexible benefits, and excellent staff travel perks.
- Why this job: Make a real impact in the aviation industry with your data skills and innovative mindset.
- Qualifications: Experience in data analytics, strong Python and SQL skills, and a degree in a relevant field.
- Other info: Hybrid working model with a dynamic team focused on continuous improvement.
The predicted salary is between 36000 - 60000 ÂŁ per year.
We are easyJet – a FTSE-100 listed, £multi‑billion low‑cost airline that serves tens of millions of customers every single year. We fly more than 1,207 routes, connecting 38 countries across Europe, and employ more than 18,000 colleagues. We’re on a mission to make low‑cost travel easy – and whatever your role here, you’ll connect millions of people to what they love using Europe’s best airline network, great value fares, and friendly service.
Read on if you:
- Have experience working in a fast‑paced data analytics or data science environment
- Confidently enjoy turning complex data into clear insight that drives real‑world decisions
- Can be in the Luton (Capability Green) office 3 Ă— per week
The Team
Our Engineering and Maintenance Supply Chain team manages more than 500,000 parts transactions every year, overseeing aircraft material worth over $250 m across our European network and an annual spend exceeding ÂŁ150 m. This is a highly driven team operating at pace, focused on maximising aircraft availability while reducing inventory cost and keeping our operation moving.
The Role
As a Supply Chain Data Analyst, you’ll sit at the heart of our Engineering and Maintenance Supply Chain function. Your mission is to use data, analytics and automation to improve aircraft availability, reduce technical disruption and help the business make smarter decisions faster. You’ll act as a data lead for Supply Chain, shaping how we forecast material, model inventory, plan strategically and design our network. You’ll work closely with Supply Chain stakeholders and our Data Science and Analytics teams to turn insight into action.
What you’ll be doing:
- Identify opportunities where data and analytics can improve operational performance and translate these into impactful dashboards and data products
- Build and support scalable data solutions that deliver clear, actionable insight
- Lead data investigations, performing root‑cause analysis and clearly communicating outcomes
- Drive standardisation and best practice across analysis, methodology and reporting
- Support forecasting, inventory modelling, strategic planning and network design activity
- Deliver ad hoc analysis to support decision making at all levels, including senior leadership
- Manage multiple projects independently while maintaining accuracy and pace
- Stay curious and up to date with best practice in analytics, governance and innovation
What we’re looking for:
- Proven experience in a high‑pressure, fast‑moving data analytics environment
- Familiarity with Skywise, AMOS, and other modern data management platforms (desirable)
- Strong Python and SQL skills with solid data management and governance knowledge
- Broad technical systems and platform experience, including data visualisation tools such as Tableau, Power BI, Qlik Sense or ThoughtSpot, distributed data platforms such as Databricks, and modern data science and cloud environments covering Big Data, analytics tooling and the MLOps lifecycle
- Strong understanding of data science methodologies, cloud environments and the analytics lifecycle
- Excellent communication skills with the ability to simplify complex concepts for non‑technical audiences
- Experience working in Agile environments and across multiple stakeholder groups
- A degree in a scientific or engineering discipline or equivalent commercial experience
- Supply chain or airline experience
What you’ll get in return:
- Up to 20 % bonus
- 25 days holiday
- BAYE, SAYE and Performance Share Schemes
- Life assurance
- Flexible benefits package
- Excellent staff travel benefits
Practicalities:
This full‑time role will be based in Luton and will be 40 hours per week. We support hybrid working and we spend 60% of our time per month in the office.
Reasonable Adjustments:
At easyJet, we are dedicated to fostering an inclusive workplace that reflects the diverse customers we serve across Europe. We welcome candidates from all backgrounds. If you require specific adjustments or support during the application or recruitment process, such as extra time for assessments or accessible interview locations, please contact us at ma.recruitment@easyjet.com. We are committed to providing reasonable adjustments throughout the recruitment process to ensure accessibility and accommodation.
Supply Chain Data Analyst employer: easyJet Airline Company PLC
Contact Detail:
easyJet Airline Company PLC Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Supply Chain Data Analyst
✨Tip Number 1
Network like a pro! Reach out to current employees at easyJet on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing the Supply Chain Data Analyst role.
✨Tip Number 2
Prepare for the interview by brushing up on your Python and SQL skills. Be ready to discuss how you've used data to drive decisions in past roles, as this will show you're a perfect fit for the fast-paced environment at easyJet.
✨Tip Number 3
Showcase your analytical mindset! Bring examples of dashboards or data products you've created that had a real impact. This will demonstrate your ability to turn complex data into actionable insights, which is key for the role.
✨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 the easyJet team.
We think you need these skills to ace Supply Chain Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Supply Chain Data Analyst role. Highlight your experience in data analytics and any relevant tools you've used, like Python or SQL. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about the role and how you can contribute to our mission at easyJet. Keep it concise but impactful – we love a good story!
Showcase Your Data Skills: In your application, don’t forget to showcase your data skills. Mention specific projects where you've turned complex data into actionable insights. We’re all about making smarter decisions faster, so show us how you can help with that!
Apply Through Our Website: We encourage you to apply through our website for the best experience. It’s straightforward and ensures your application gets to the right people. Plus, you’ll find all the info you need about the role there!
How to prepare for a job interview at easyJet Airline Company PLC
✨Know Your Data Tools
Make sure you brush up on your Python and SQL skills before the interview. Familiarity with data visualisation tools like Tableau or Power BI will also give you an edge. Be ready to discuss how you've used these tools in past roles to drive insights.
✨Understand the Supply Chain Landscape
Get a good grasp of supply chain dynamics, especially in the airline industry. Research easyJet's operations and think about how data analytics can improve their processes. This will show your genuine interest and understanding of the role.
✨Prepare for Scenario Questions
Expect questions that ask you to solve real-world problems using data. Practice articulating your thought process clearly, especially when it comes to root-cause analysis and decision-making based on data insights.
✨Showcase Your Communication Skills
Since you'll be working with various stakeholders, it's crucial to demonstrate your ability to simplify complex data concepts. Prepare examples where you've successfully communicated technical information to non-technical audiences.