Top Tech Jobs & Startup Jobs in Chicago, IL

Provide proactive outreach and promptly resolve Reference Lab customer concerns and testing issues. Collaborate across IDEXX teams to research problems, maintain strong internal and external relationships, support quality management and compliance, and participate in team development and knowledge sharing. Communicate clearly and empathetically, use Microsoft Office and other systems, ensure data accuracy, and meet physical job requirements including extended computer/phone use and occasional lifting.

Design, develop, and deliver engaging, scalable learning solutions using multimedia and user-centered approaches. Manage ID projects, stakeholder engagement, LMS integration, eLearning standards (SCORM/AICC/xAPI), and apply adult learning theory, Design Thinking, Agile methods, and AI tools to create blended and virtual training for global employees.

Manage a mid-sized global Salesforce (Lightning) instance using Sales and Service Cloud. Translate business needs into configurations, provide daily administration, backups, security, capacity planning, reporting, user support, testing, training, documentation, and stakeholder liaison. Participate in development tasks and on-call rotation to ensure system stability and feature delivery.

Provide phone-based customer support to IDEXX veterinary customers, answering 50–70 calls daily, explaining lab test results, coordinating follow-up tests and sample logistics, and resolving issues quickly while using computer systems and Microsoft Teams—all in both French and English.

Manage and grow the VetSoft Payments engineering team, focusing on scalable, secure payments systems while leading and mentoring a distributed engineering team.

Lead design and implementation of end-to-end ELT pipelines and transformation layers (dbt) to produce curated, reporting-ready datasets. Define data models, governance, metadata, lineage, and engineering standards. Partner with cross-functional teams to translate requirements, optimize performance and costs (cloud DW like Snowflake), and grow a data architecture practice that supports BI, self-service analytics, and AI agents.

Design, implement, validate, and deploy advanced machine learning and statistical models across the data science pipeline. Collaborate with product and engineering, mentor peers, translate research into production, and deliver high-impact business insights using large-scale and distributed data platforms.