About this role
Excel & Automation Ninja Wanted to join our Data department Location: Bucharest As a Junior Data Operations Analyst you’ll be handling massive amounts of unstructured and complex data provided by some of the world’s largest companies. Xeneta provides data and market intelligence for the air cargo industry , working with shippers, freight forwarders and airlines to create greater transparency in the market. We gather large amounts of data on freight rates and market movements, helping our customers benchmark performance, understand market developments and make better decisions around pricing and supply chains. As data standards are limited across the freight industry, you will work closely with customers and internal stakeholders to understand their data, ensure the quality and structure required for rate benchmarking, and support data-related questions throughout the customer journey. Beyond processing data, we expect you to develop a strong understanding of what the data represents, recognize when something does not make sense from an air freight perspective, and help translate customer requirements into reliable data solutions. You will also use Python, Excel and automation to improve how we process and validate data, reduce repetitive manual work, and contribute to new tools and processes that improve data quality and team efficiency. Bring your interest in air freight, Excel and Python tool suite , a problem-solving and analytical mindset, and a keen eye for detail, and join our team! Understand and process complex global air freight data to ensure accurate and timely delivery of data to our platform. Develop a strong understanding of our customers’ data, business requirements and use cases, working closely with Customer Success and Sales to answer data requests throughout the procurement lifecycle, including tender / RFQ, contract management, rate updates, spend analysis and budgeting. Build and apply your understanding of air freight operations, market dynamics and pricing , including spot and long-term markets, to interpret data, investigate unexpected patterns and structural changes, and identify potential data-quality issues. Use Python and Excel to process, validate and automate recurring data workflows , reducing manual work and improving scalability, reliability and data quality. Identify repetitive or manual processes and help develop automated solutions that allow the team to focus more on exceptions, investigations and customer needs. Work with customers and internal stakeholders, including Data Science, Market Analysis, Tech and Product , to understand and resolve data-quality issues and develop new data management solutions and actionable insights that improve the customer experience.