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A leading shopping rewards company is looking for a Data Engineer in Madrid. You will design, develop, and maintain data solutions, working with millions of data points and utilizing AWS Big Data services. Required skills include expertise in ETL processes, cloud platforms, and programming languages like Python and Scala. The company offers 32 days of vacation and a flexible working scheme.
Global Savings Group (GSG) is Europe’s leading shopping rewards and recommendation company.
Our mission is to create rewarding moments for consumers and empower them to make the best shopping decisions in a smart, fair, and enjoyable way.To achieve that, we run market-leading platforms that provide our users with the best savings, cashback, deals , shopping inspiration, and trustworthy reviews from real users.
We have over 7 0 nationalities represented among 1000+ talented colleagues spanning 10 countries , welcoming very diverse backgrounds which range from tech enthusiasts to online marketers, key account managers, or editors.
With us, you will be able to work on projects with an international footprint, leaving your mark in the industry and becoming a true driver of change.
We are looking for a Data Engineer to join our team and help integrate the different brands in Global Savings Group. The Data Domain is part of our Product and Technology team and is autonomous and co-functional, consisting of 30 people on 4 different teams operating in an agile and customer centered environment, mainly working with but not exclusive to AWS Big Data solutions. We need a new Data Engineer to help design, develop, and maintain data solutions to manage and convert multiple data sources into actionable intelligence that our stakeholders can use to continually improve our service for our users. The new Data Engineer will continue our efforts to collect millions of events from the frontend and backend of dozens of websites our company operates, fetch financial data from hundreds of partners to consolidate them into revenue metrics and targets for our commercial teams and work with marketing data from internal and external sources to create efficient marketing funnels.