Salary
💰 CA$150,000 - CA$180,000 per year
Tech Stack
AWSDynamoDBETLGraphQLIoTJavaScriptNode.jsPostgresPythonTerraform
About the role
- Design and build backend solutions using Python, delivering reliable and performant services integrated with data pipelines and geospatial analytics.
- Leverage large-scale data system experience to architect features that depend on dynamic, real-time, and batch data processing from IoT, satellite, and drone sources.
- Build serverless backend services on AWS (Lambda, API Gateway, DynamoDB, S3) following domain-driven design and event-driven architecture.
- Define and manage infrastructure using Infrastructure as Code (Terraform) and DevOps tools to ensure resilience and scalability.
- Contribute to building performant REST and GraphQL APIs for external clients and internal tools.
- Write clean, testable code and integrate with CI/CD pipelines; implement monitoring, logging, and error tracking for platform health.
- Shape end-to-end product architecture, contribute to technical strategy, deliver production-grade features across a modern stack.
- Provide technical mentorship and thought leadership across the Engineering team; collaborate with product teams to deliver impactful features.
Requirements
- 7-10 years of professional experience in backend development, with a strong data engineering focus.
- Deep experience in Python or Node.js
- Proven experience building scalable serverless applications on AWS (e.g. Lambda, DynamoDB, S3, API Gateway).
- Solid understanding of data engineering principles, including ELT/ETL pipelines, real-time processing, and time-series data management.
- Experience designing and maintaining APIs (REST and GraphQL) and integrating with complex backend systems.
- Strong database knowledge, both relational (PostgreSQL) and non-relational (DynamoDB, DuckDB, etc.)
- Familiarity with DevOps and IaC using Terraform or similar tools.
- Experience working in cross-functional teams and collaborating across the product lifecycle.
- Deep understanding of software engineering best practices: testing, CI/CD, Git workflows, and documentation.
- Impact-driven professional excited by geospatial IoT, real-time insights, and predictive capabilities.
- Must be legally authorized to work in Canada (application form asks 'Are you legally authorized to work in Canada?')