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Tecsys

SaaS supply chain software for omnichannel

Data Platform 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 real-time data pipelines, is required.
  • Strong Terraform skills and experience managing cloud infrastructure on AWS.
  • Practical knowledge of Kubernetes and Helm, and containerization with Docker.
  • Proficiency in Python (PySpark) and/or Java, and strong SQL skills for data validation and troubleshooting.
  • Experience with Git-based workflows and CI/CD pipelines in a multi-repository environment.
  • Understanding of data quality concepts, ETL/ELT processes, and data observability.
  • Experience working in Agile teams in collaboration with data platform developers and product owners.
  • Strong analytical, problem-solving, and communication skills.
  • Applicants must be Canadian citizens, Canadian permanent residents, or hold a valid Canadian work permit.

Responsibilities

  • Provision and scale AWS accounts and Databricks workspaces using Terraform across multiple regions and environments, while managing remote state and environment-specific configurations.
  • Maintain Helm charts and Kubernetes jobs used to onboard new customer environments and deploy the application layer to provisioned workspaces.
  • Build and maintain Docker images and Java/Maven build pipelines, and publish artifacts to internal artifact and container registries.
  • Integrate build, test, and deployment processes into CI/CD pipelines, while improving release and delivery management across multiple interconnected code repositories.
  • Manage secrets and credentials securely using cloud secrets-management services and Kubernetes, without storing them in source code.
  • Design, develop, and maintain Databricks jobs and pipelines, including data curation, transformations, and initial bulk-loading processes.
  • Develop and operate real-time streaming and change data capture (CDC) pipelines across ingestion and transformation layers using Spark Structured Streaming.
  • Develop and scale end-to-end data flows across Bronze, Silver, and Gold layers, adapting pipelines to handle new data sources and schema changes as the platform grows.
  • Develop and maintain reusable pipeline components and frameworks to onboard new data flows quickly.
  • Optimize Databricks clusters and SQL warehouses for cost and performance, while managing catalogs, schemas, and access 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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