David García Álvarez

David García Álvarez has a diverse and extensive work experience in the field of software engineering. David is currently working as a Staff Software Engineer at JOOR. Prior to this, they worked at Smart Protection as a Staff Software Engineer, where they developed and maintained a cloud platform and made decisions regarding product evolution and technology selection. David'smain technologies at Smart Protection included Python, Docker, AWS, PostgreSQL, and Terraform.

Before their role at Smart Protection, David worked as a Senior Backend Software Engineer at the same company. Prior to that, they were a Backend Software Engineer at Tuenti, where they developed and maintained the software platform using PHP, Python, and Java. David'sresponsibilities included developing and maintaining multiple services and tools, such as user service, GDPR services, and internal tools to help other developers be more productive.

David also has experience as a Backend Software Engineer at BEEVA, where they developed a Database as a Service (DBaaS) and worked on BBVA Data & Analytics projects as a Big Data Engineer. David'smain programming languages at BEEVA were Scala and Python, and they worked with Cloudera for execution clusters.

In addition to these roles, David has worked as a Backend Developer at Sopra Steria, where they developed an API REST for Sanitas APP and WEB using Java, Spring, and Oracle. David started their career as an intern at BAYES FORECAST and practiced in the role of programming at ACTIVE Business & Technology, S.L.

David García Álvarez completed their education with a Grado degree in Ingeniería informática from the Universidad Complutense de Madrid. David obtained this degree between 2011 and 2015. In addition to their formal education, David also holds several certifications. These include Apache Spark Essentials from Linux Academy in November 2017, Big Data Analysis with Scala and Spark from Coursera in August 2017, Functional Programming Principles in Scala from Coursera in August 2017, Machine Learning from Coursera in August 2017, and Big Data on AWS from Qwiklabs in January 2017.