Miguel Angel Pozos Sr, BS EMBA, CSM

Quality Assurance Engineer at Smartwyre

Miguel Angel Pozos Sr, BS EMBA, CSM has a diverse range of work experience in the field of software development and quality assurance. Miguel Angel is currently employed at Smartwyre as a Quality Assurance Engineer, where they maintain and develops automation frameworks and tests critical features. Previously, they worked at Booz Allen Hamilton as an Associate Software Developer, Trelar as a Quality Assurance Manager / ScrumMaster, RF Code as a Senior Software Verification Engineer, Metal Networks as a Quality Assurance Manager, Mitratech as a Product Quality Manager, vcfo as a QA Engineer, Identropy Inc. as a QA Engineer, Allied Professionals and Consultants as an IT Security Specialist, and IBM as a Software Engineer. Throughout their career, Miguel has demonstrated strong skills in automation, testing, and leadership, taking on various roles and responsibilities in each position.

Miguel Angel Pozos Sr, BS EMBA, CSM has a strong educational background in business and computer science. Miguel Angel started their education journey in 1997 at The University of Texas at Austin, where they obtained a Bachelor of Science degree in Computer Science. After completing their undergraduate studies in 2002, Miguel built a solid foundation in the field of technology.

Realizing the importance of business acumen, Miguel decided to pursue further education. From 2011 to 2013, they enrolled in the Executive program at Texas McCombs School of Business. In this program, they completed a Master of Business Administration degree, further enhancing their knowledge and skills in the business domain.

Overall, Miguel Angel Pozos Sr's educational journey showcases their dedication to both technology and business, providing him with a comprehensive skillset in these areas.

Location

Austin, United States

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Smartwyre

Smartwyre connects you with up-to-date product, price, and rebate program data from the crop protection and seed suppliers you know and trust. This means you can calculate earned and forecast rebates with greater accuracy, and remove uncertainty from y...


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11-50

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