Our client is a multinational consultancy looking for a Data Engineer in Madrid or Barcelona who will be an integral part of the project teams working to drive top-line growth for their clients. As a Data Engineer, you will be responsible for large data management processes during client projects. You will develop and automate robust processes to extract, transform, and load large, scattered, and unstructured data sets into clean and powerful analysis cubes, which form a fundamental basis of their business recommendations. In addition, you will identify, tackle, and implement internal data process and technology improvements.
Key Responsibilities:Generate large and multi-dimensional analysis cubes based on client data.Validate data and ensure completeness, correctness, and relevance for meaningful analyses.Develop and automate analytical tools based on the generated cubes that provide Marketing, Sales, and Pricing insights.Advise and support clients on how to design, implement, and automate robust ETL processes.Work with internal and external business and technology experts across the world.Detect, solve, and implement internal process and technology improvements as well as create, optimize, and maintain new and existing data transfer channels.Requisitos:Basic Qualifications:Master's or bachelor's degree (business, economics, computer science, or engineering preferred).Proven capabilities to build and maintain large and complex data sets.Experience in structuring and automating ETL processes based on scattered and unstructured data sources.Experience with relational data management software and languages (especially SQL).Proven knowledge about analytical/BI software and languages (e.g., Tableau, PowerBI, Python, R).Familiarity with big data technologies (e.g., NoSQL databases, Hadoop and distributed file systems, or stream processing technologies) is a strong plus.Sharp analytical and problem-solving mindset.Pro-active, reliable attitude and enthusiasm for working in teams.Ventajas:Hybrid position (3 days remote, 2 days in the office). Friday afterwork. Flexibility.
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