At a Glance
- Tasks: Ensure finance data is clean and ready for migration to a new system.
- Company: AerFin, a leader in aviation solutions with a high-performance culture.
- Benefits: Pension scheme, employee assistance programme, 28 days annual leave, and social events.
- Other info: Join a diverse team committed to innovation and excellence.
- Why this job: Make a real impact on data quality in a dynamic aviation environment.
- Qualifications: Experience in finance data quality and strong organisational skills required.
The predicted salary is between 35000 - 45000 € per year.
12-month fixed-term contract – Full time – Location: Newport or Crawley | Hybrid
About AerFin
AerFin is breathing new life into aviation. We buy, sell, lease and repair aircraft, engines, and parts to maximise the value for their owners and provide a lower-cost supply of material to our airline, lessor and MRO customers. Through our deep technical expertise and high-performance culture, we deliver confidence-inspiring quality, safety and value to our customers. Our blend of industry expertise and experience – today’s insight and tomorrow’s foresight – gives us a unique perspective on our industry that is trusted by over 600 customers across six continents. With regional hubs in Europe, Asia and the USA we’re perfectly placed to keep fleets flying and get deals done.
About The Role
We are looking for a Finance Data Quality Analyst on a 12-month fixed-term-contract to ensure AerFin’s finance data is clean, consistent, and ready for migration to a new finance system. This role is critical to reducing implementation risk and enabling reliable reporting from day one. This position combines hands‑on data work with coordination and leadership. You will not only deliver data profiling and cleansing activities, but also work closely with SMEs and data owners across the business to define data standards, rules, and cleansing plans. Working collaboratively with Finance, Operations, and IT/Transformation teams, you will drive a structured and measurable data cleanse programme aligned to key milestones.
What You’ll Do
- Profile current finance data and create a prioritised data quality issue log (e.g. duplicates, missing fields, inconsistent coding)
- Cleanse and standardise key master data (e.g. Chart of Accounts, cost centres, suppliers, customers, tax codes)
- Lead the delivery of a structured data cleansing plan, assigning actions and tracking progress against defined timelines
- Collaborate with SMEs to capture business rules and translate them into clear data standards and validation rules
- Drive accountability for data ownership and issue resolution across stakeholders
- Support the cleansing and validation of transactional data (e.g. AP/AR, asset registers, inventory data)
- Define and implement data governance frameworks (ownership, validation rules, naming conventions, approval workflows)
- Prepare data mapping and reconciliation packs to support system migration
- Support test cycles, track data defects, and coordinate resolution
- Provide clear reporting on progress, risks, and readiness for migration
What We’re Looking For
- Experience in data quality, cleansing, or migration within a finance environment
- Strong understanding of finance data (GL, AP, AR, fixed assets, cost centres; inventory desirable)
- Proven experience coordinating data cleansing activities across multiple stakeholders
- Ability to translate business knowledge into structured data standards and rules
- Strong organisational skills with the ability to manage delivery against timelines
- Advanced Excel skills, including working with large datasets (Power Query preferred)
- High attention to detail and strong documentation skills
- Confident stakeholder management and ability to drive accountability
- Experience using Power BI for data quality reporting and dashboard creation is a plus.
- Familiarity with data governance frameworks and master data management principles is beneficial
In return we offer:
- Pension Scheme
- Employee Assistance Program (EAP)
- 28 days of annual leave with an option to buy or sell an additional 5 days per year
- Social events and much more
AerFin is an equal opportunities employer, which cultivates opinion, listens to all views with respect, recognises people based on their merits without bias and embraces diversity.
Finance Data Quality Analyst - FTC in Crawley employer: AerFin
AerFin is an exceptional employer that fosters a high-performance culture and values the contributions of its employees. With a commitment to employee growth, we offer a supportive work environment in Newport or Crawley, where you can thrive through collaboration and innovation. Our comprehensive benefits package, including a pension scheme and generous annual leave, alongside our dedication to diversity and inclusion, makes AerFin a rewarding place to build your career in the aviation industry.
StudySmarter Expert Advice🤫
We think this is how you could land Finance Data Quality Analyst - FTC in Crawley
✨Tip Number 1
Network like a pro! Reach out to people in the finance and data quality space, especially those who work at AerFin or similar companies. A friendly chat can open doors and give you insights that might just land you an interview.
✨Tip Number 2
Prepare for the interview by brushing up on your data quality knowledge. Be ready to discuss your experience with data cleansing and governance frameworks. We want to see how you can bring your skills to the table and help us keep our finance data top-notch!
✨Tip Number 3
Show off your Excel skills! If you’ve got experience with Power Query or handling large datasets, make sure to highlight that. We love seeing candidates who can dive into data and come out with clean, actionable insights.
✨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 AerFin.
We think you need these skills to ace Finance Data Quality Analyst - FTC in Crawley
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Finance Data Quality Analyst. Highlight your experience in data quality, cleansing, and migration within a finance environment. We want to see how your skills align with what we're looking for!
Showcase Your Skills:Don’t forget to mention your advanced Excel skills and any experience with Power BI. These are key for the role, so let us know how you've used them in past projects. We love seeing practical examples!
Be Clear and Concise:When writing your application, keep it clear and to the point. Use bullet points where possible to make it easy for us to read through your achievements and experiences. We appreciate a well-structured application!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at AerFin
✨Know Your Data Inside Out
Before the interview, make sure you brush up on your finance data knowledge. Understand key concepts like GL, AP, AR, and fixed assets. Being able to discuss these topics confidently will show that you're not just familiar with the terms but can also apply them in a practical context.
✨Showcase Your Organisational Skills
Prepare examples of how you've managed data cleansing activities in the past. Be ready to discuss specific projects where you coordinated with multiple stakeholders. This will demonstrate your ability to keep things on track and meet deadlines, which is crucial for this role.
✨Familiarise Yourself with Data Governance
Since the role involves defining data standards and governance frameworks, it’s essential to understand these concepts. Brush up on best practices in data governance and be prepared to discuss how you would implement these in your work at AerFin.
✨Excel Skills are Key
Given the emphasis on advanced Excel skills, practice using Power Query and working with large datasets. Be ready to talk about your experience with Excel during the interview, perhaps even sharing a specific example of how you used it to solve a data issue.
