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Tecsys

SaaS supply chain software for omnichannel

Data Engineer - DevOps

Data EngineeringConfirmed live in the last 24 hours
Full-timeMontreal, QC, CanadaNo salary listed

About the Job

Requirements

  • Hands-on experience with Databricks and Apache Spark, including building batch or streaming data pipelines, is mandatory.
  • Strong Terraform skills and comfort managing cloud infrastructure on AWS.
  • Working knowledge of Kubernetes and Helm, and containerization with Docker.
  • Proficiency in Python (PySpark) and/or Java, plus strong SQL for data validation and troubleshooting.
  • Experience with Git-based workflows and CI/CD pipelines in a multi-repository codebase.
  • Understanding of data quality, ETL/ELT, and data observability concepts.
  • Experience working in Agile teams alongside Data Platform Developers and Product Owners.
  • Fluency in written and spoken English is essential for communicating effectively with clients, suppliers, business partners, and colleagues outside of Quebec.

Responsibilities

  • 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.
  • Design, build, and maintain Databricks jobs and pipelines, including data curation, transformation, and initial bulk-load workflows.
  • Develop and operate real-time streaming and change data capture (CDC) pipelines across the ingestion and transformation layers using Spark Structured Streaming.
  • Build and evolve end-to-end data movement across the Bronze, Silver, and Gold data layers, extending pipelines to handle new sources and schema changes as the platform grows.
  • Develop and maintain reusable pipeline components and frameworks so new data workflows can be onboarded and shipped quickly.
  • Tune clusters and SQL warehouses for cost and performance, and manage catalog, schema, and access governance across environments.
  • Collaborate with Data Platform Developers, Product Owners, and business stakeholders in an Agile environment to deliver high-quality data products.

About the Company

Tecsys

SaaS supply chain software for omnichannel

Tecsys provides cloud-based supply chain software that helps organizations manage complex, omni-channel operations. Its products cover the end-to-end supply chain—from demand planning to order fulfillment—delivered primarily as software-as-a-service (SaaS) with professional services and training. The platform increases efficiency and visibility by offering integrated workflows for front-line workers and back-office planners, serving sectors like healthcare, retail, and logistics providers. Unlike some competitors, Tecsys combines a long-standing track record (founded in 1983) with a broad product suite that emphasizes both planning and execution across diverse industries. The goal is to help customers navigate rapidly changing market conditions and improve operational performance across the entire supply chain.

Company size
501-1,000
Company stage
IPO
Headquarters
Montreal, Canada
Founded
1983

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