Finance Data Analyst

About Us

Planet is a leading technology company transforming payments by putting customer experience first. We offer integrated solutions that include payment processing, VAT refunds, dynamic currency conversion, and management services for merchants in the Retail and Hospitality sectors worldwide.

In recent years, we have experienced significant growth, expanding our services and global presence. With strong private equity investors, Advent International and Eurazeo, we have the financial capital and expertise to grow our capabilities and reach through acquisitions.

Our mission is to create a world of connected commerce where payments are simple, secure, and seamless, enabling our partners to deliver exceptional experiences to their customers.

Role Overview

Are you a recent graduate looking to turn what you learned at university into real-world experience? This four-month, full-time fixed-term opportunity will give you hands-on experience working on an important Finance data transformation project at Planet.

You will help us build trusted Finance data foundations, working with real business data and gaining practical exposure to data analysis, data quality, governance, Snowflake and AI-assisted tools. You do not need to arrive as an expert. We are looking for people with strong analytical potential, curiosity, attention to detail and a desire to learn.

What you will do

• Work with real Finance data, reviewing and validating information to ensure it is accurate, consistent and reliable.
• Investigate data-quality issues, such as duplicate, incomplete or inconsistent records, and help identify their underlying causes.
• Learn and apply data-governance principles, using agreed definitions and quality rules and identifying opportunities to improve them.
• Use tools such as Snowflake and AI-assisted workflows to research, compare and investigate data with support from experienced colleagues.
• Use AI responsibly to accelerate analysis while applying your own judgement and evidence before reaching conclusions.
• Document your findings and decisions, helping us build data-quality processes that are clear, repeatable and auditable.
• Collaborate with Finance, Data and Technology teams, gaining exposure to how different areas of an international technology business use and manage data.

Who you are

• You are a recent graduate or postgraduate, ideally in Data Analytics, Data Science, Finance, Business Analytics, Information Systems or another relevant quantitative discipline.
• You enjoy working with data, solving problems and understanding why something does not look right.
• You bring strong analytical thinking and attention to detail.
• You are curious and comfortable learning new technologies, tools and business concepts.
• You approach problems methodically and use evidence to support your conclusions.
• You are interested in how AI and data technologies can solve real business problems.
• Any exposure to Excel, SQL, Snowflake, Python, Streamlit or data visualisation is an advantage, but we do not expect you to know everything from day one.

What you will gain

Over the four months, you will gain practical experience in:

• Data analytics and data quality within a global technology business.
• Snowflake and modern data workflows used to investigate and manage business data.
• AI-assisted analysis and the responsible use of AI to solve real business problems.
• Finance transformation, seeing how trusted data supports reporting, analytics, automation and AI.
• Data governance and stewardship, including how organisations define, validate and protect important data.
• Cross-functional collaboration across Finance, Data and Technology.

Why Planet

Planet is an equal opportunity employer where diversity is valued, and all employment is decided based on qualifications, merit, and business need.

Come and grow your career in the most exciting, fast paced technology market, with a business that delivers feel-good connected commerce.

We would love to hear from you – Apply now.

At Planet, we embrace a hybrid work model, with three days a week in the office.
 

Reasonable accommodations may be made in order to allow for an individual to perform the essential functions of this role successfully.