LATIN AMERICA

March 19, 2025
Svitla Systems Inc. is looking for a Cloud Data Analytics Applications Engineer for a full-time position (40 hours per week) in Argentina and Costa Rica.
Our client is a global leader in designing, developing, and automating complex diagnostics, inspection, and test processes across medical & life sciences, transportation, and specialty industrial sectors. With over 70 years of innovation experience, the company operates in more than 40 locations worldwide. They deliver a range of offerings, from the most complex diagnostic tools used in life sciences to the development and testing of adaptive safety systems in electric vehicles, the inspection of advanced microprocessors for functional integrity, and much more. Their customers include Fortune 100 leaders and disruptive innovators, including 3M, Abbott, Boston Scientific, Electrolux, GM, Medtronic, Thermo Fisher Scientific, and Volkswagen.

REQUIREMENTS:

• Bachelor’s/Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• Proven experience with telemetry and analytics tools.
• Knowledge with big data tools (Hadoop, Spark, Kafka).
• Strong knowledge of cloud platforms (AWS, Azure, GCP) and on-premises infrastructure.
• Understanding anomaly detection, machine learning, and AI integration.
• Experience with programming languages such as Ruby, Python, SQL, NoSQL, C++, C#, and Scala.
• Familiarity with data visualization tools and techniques.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills.

• Come up to speed with the data analytics and remote monitoring service to drive the design and implementation of new features.
• Research and integrate additional and/or alternative technologies to facilitate compatibility with cloud and on-prem environments.
• Build and maintain data pipelines to ensure data accuracy and consistency.
• Develop and support robust data visualizations, alerts, and notification systems.
• Design and implement security/privacy protocols to protect sensitive data.
• Enhance current features such as anomaly detection; contribute other machine learning and AI capabilities to the service.
• Ensure the monitoring service is highly available, scalable, and performing.
• Stay updated with the latest trends and technologies in data analytics, machine learning, and AI.
• Collaborate with cross-functional teams to understand requirements and deliver solutions that meet business needs.