ZS

Toronto
15,000 Total Employees
Year Founded: 1983

ZS Offices

Hybrid Workplace

Employees engage in a combination of remote and on-site work.

The Flexible & Connected model is our ZS standard. ZSers decide where it makes the most sense for them to work each day given client or teamwork.

Typical time on-site: 3 days a week

Global Office Locations

Toronto

Since the Toronto office opened in 2002, ZS Canada has been partnering with local companies to help them face critical challenges and embrace opportunities through our deep expertise.

Recently posted jobs

7 Days AgoSaved
Hybrid
Toronto, ON, CAN
Artificial Intelligence • Healthtech • Professional Services • Analytics • Consulting
Design, develop, and deploy scalable LLM applications and pipelines using RAG, agentic workflows, and parameter-efficient fine-tuning. Own architecture, software development lifecycle, cloud infrastructure, governance, responsible AI guardrails, DevOps automation, testing, and deployment. Collaborate with cross-functional teams, translate business needs into technical requirements, conduct code reviews, and ensure reliable production systems using AWS, Azure, and Databricks.
10 Days AgoSaved
Hybrid
Toronto, ON, CAN
Artificial Intelligence • Healthtech • Professional Services • Analytics • Consulting
Leads the design, development, and optimization of scalable data architectures, ETL pipelines, ingestion frameworks, data quality processes, governance practices, and audit systems. Partners with cross-functional teams to translate requirements into data solutions, analyzes data for business insights, communicates recommendations, and mentors Data Engineers. The role also serves as a technical authority and supports continuous improvement across data engineering practices.
One Month AgoSaved
Hybrid
Toronto, ON, CAN
Artificial Intelligence • Healthtech • Professional Services • Analytics • Consulting
Lead design and build scalable data architectures, ETL pipelines, ingestion and data quality frameworks. Collaborate with cross-functional teams, enforce data governance, analyze data for insights, mentor junior engineers, and serve as the technical authority on data engineering best practices.