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At Tecsys, the software we deliver keeps hospitals, pharmacies and distributors supplied with what they need, when they need it. Every role here connects to that outcome.

Why This Role Matters

We're looking for a Data Platform Engineer (DevOps) to join our TecsysIQ Data & AI team. This is a hybrid role that builds and operates the cloud data platform powering our analytics and AI products on Databricks and AWS.

You will own the infrastructure-as-code and delivery pipelines that provision and deploy the platform, and the Databricks jobs and streaming pipelines that move and shape data through it. You'll partner closely with Data Platform Developers, application dev teams, and Product Owners — standing up new customer environments, evolving the CI/CD and release process, and creating and maintaining the data pipelines that keep the platform running reliably at scale. If you are equally comfortable writing Terraform and debugging a Spark Structured Streaming job, this role is for you.

What You’ll Be Part Of

Tecsys is trusted by mission-critical organizations in healthcare and distribution to power resilient, efficient and secure supply chains. We are a global provider of cloud-based, AI-driven software, publicly traded on the Toronto Stock Exchange (TSX: TCS).

Three values guide how we work. We earn trust daily by valuing the customer and acting with integrity. We build each other up by recognizing individual strengths and working as one team. And we explore boldly by staying curious and adapting for success.

You’ll join a culture driven by curiosity, continuous learning, and people who challenge what’s possible.

What You’ll Do

Platform & DevOps

• Provision and evolve AWS and Databricks accounts and workspaces using Terraform across multiple regions and environments, managing remote state and per-environment configuration.
• Own the Helm charts and Kubernetes Jobs that onboard new customer environments and deploy the application layer onto provisioned workspaces.
• Build and maintain Docker images and the Java/Maven build pipeline, publishing artifacts to internal artifact and container registries.
• Integrate build, test, and deployment into CI/CD pipelines , and improve release management and versioning across interdependent repositories.
• Manage secrets and credentials safely through cloud secret management and Kubernetes — never in source control.

Data Platform & Pipelines

• Design, build, and maintain Databricks jobs and pipelines — including data curation, transformation, and initial bulk-load workflows.