Marcia Tejeda
About Marcia Tejeda
Marcia Tejeda is a Senior Software Engineer at sennder, with a background in software engineering and computer programming. She has extensive experience in software development, particularly in Java and data analytics, and also serves as a professor at Universidad Nacional de Quilmes.
Work at sennder
Marcia Tejeda has been employed at sennder as a Senior Software Engineer since 2022. In this role, she is responsible for developing and maintaining software solutions that enhance the company's logistics and transportation services. Her expertise in software engineering contributes to the efficiency and effectiveness of the projects she undertakes.
Education and Expertise
Marcia Tejeda studied at Universidad Nacional de Quilmes, where she earned a Bachelor's degree in Information Technology from 2014 to 2021. Prior to this, she completed a University technician program in computer programming at the same institution from 2008 to 2014. Her educational background provides her with a strong foundation in software engineering and programming.
Background
Before joining sennder, Marcia Tejeda worked in various roles within the software development field. She served as a JAVA Developer at DL Consultores for seven months in 2010-2011. Following that, she worked as a Software Engineer II at Medallia from 2020 to 2021 and as a Senior Consultant Developer at Thoughtworks from 2021 to 2022.
Teaching Experience
In addition to her engineering roles, Marcia Tejeda has been a Professor at Universidad Nacional de Quilmes since 2021. She teaches courses related to software engineering and programming, sharing her knowledge and experience with students in Buenos Aires, Ciudad Autónoma de Buenos Aires, Argentina.
Technical Contributions
During her time at Medallia, Marcia was part of the Text Analytics team, where she developed RESTful APIs and utilized technologies such as Java 11, Apache Kafka, and Elasticsearch. She contributed to processing and analyzing large volumes of text data from user surveys using data science models, enhancing the team's capabilities in text analytics.