Data Engineer

• Experience in data engineering and working with large volumes of information.
• Solid knowledge of Python and T-SQL for data manipulation and analysis.
• Experience in the development and optimization of ETL pipelines.
• Knowledge of data architectures and information exploration and validation techniques.
• Analytical and problem-solving skills, with an orientation toward continuous improvement.
• Good communication skills and the ability to collaborate with multidisciplinary teams.

• Experience with Azure Databricks and Azure Data Factory.
• Knowledge of MLflow and MLOps processes.
• Knowledge of Machine Learning techniques, such as clustering, decision trees, and neural networks.
• Experience in data visualization and presentation using Power BI.

• University degree in Data Science, Computer Science, Statistics, or related disciplines.

• High level of English, both spoken and written.

• Permanent contract with end client.
• Competitive salary according to experience.
• 100% REMOTE from Spain.
• Joining an international and multidisciplinary environment.

We are looking for a Data Engineer to join the data team. You will develop and implement ETL pipelines, work with large volumes of information, and develop automated models and processes, collaborating closely with technical and business teams.

• Drive the transformation of data into solutions that improve the business
• Develop efficient pipelines and convert large volumes of data into value

• Identify new business opportunities through the analysis and exploitation of company data.
• Design, develop, and optimize ETL pipelines to extract, transform, and load data from multiple sources.
• Evaluate the quality, accuracy, and reliability of data, as well as improve collection and automation processes.
• Develop data models and algorithms to obtain valuable information from large datasets.
• Collaborate with development, database, architecture, and DevOps teams to implement automated solutions and MLOps processes.
• Monitor model performance and guarantee data quality and accuracy.
• Work with business, digital product, and analytics teams to identify opportunities for optimization and continuous improvement.
• Communicate results, proposals, and benefits of the developed solutions to the different stakeholders.