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Design, develop, and maintain scalable data pipelines and ETL processes using Azure services. Collaborate with data analysts and scientists to ensure data accessibility and troubleshoot pipeline failures.
At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.
Seeking a skilled and motivated Data Engineer with expertise in Azure Data Factory (ADF) to join our growing data team. The ideal candidate will be responsible for designing, developing, and maintaining scalable data pipelines and ETL processes using Azure services. You will work closely with data analysts, data scientists, and business stakeholders to ensure data is accessible, reliable, and optimized for analytics and reporting.
Prefered qualifications
Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of over 420,000 team members in more than 50 countries. We deliver end-to end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations.
At Capgemini Mexico, we aim to attract the best talent and are committed to creating a diverse and inclusive work environment, so there is no discrimination based on race, sex, sexual orientation, gender identity or expression, or any other characteristic of a person. All applications welcome and will be considered based on merit against the job and/or experience for the position.
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