About Us: Skyward Wildfire Technologies is a dynamic startup based in British Columbia, Canada on a mission to make the world a safer place. Our cutting-edge technology is designed to attenuate lightning storms and reduce the occurrence of wildfires, protecting communities and the environment. We're combining innovative science, big data, and machine learning to tackle one of nature's most unpredictable and devastating forces—lightning. If you’re passionate about making a real-world impact with your data skills, we want you on our team!

Mission: Skyward’s mission is to save lives, ecosystems, communities, and gigatonnes of emissions by preventing lightning from causing out-of-control fires on high-risk days. Lightning causes 58% of fires in Canada and 93% of burned area/emissions. In 2023 Canadian wildfires emitted GHG equivalent to India, 3x the emissions of Canada’s entire economy. Hotter and drier forests are primed to make lightning ignition 40-60% more likely per 1°C of warming. Preventing lightning wildfires is the lowest cost option globally for Gigatonne scale emissions reduction.

About the Role: We are looking for a Cloud Architect with strong Python expertise to design and evolve a cloud-native, layered data platform. The platform is structured around clearly separated layers that allow rapid extension and low coupling between components.

The architecture includes a data layer where information is stored in databases and object storage buckets, a processing layer where data is transformed using containerized workloads, a service layer exposing data products through APIs, and a frontend layer that visualizes results, including map-based views. A key requirement is that these layers are abstracted and orchestrated, making it easy to add new data sources, processing pipelines, or services without impacting the rest of the system.

Responsibilities:

• Design and maintain a modular, layered cloud architecture using Python-based frameworks.
• Define abstraction patterns (interfaces, adapters, schemas) to support plug-and-play data sources, processors, and services.
• Build and operate containerized data processing components (Docker), ensuring portability, scalability, and reproducibility.
• Design orchestration for end-to-end workflows, including scheduling, dependencies, retries, and monitoring.
• Develop and guide Python API services (e.g., FastAPI, Flask, Django) for secure and scalable data access.
• Select and integrate managed cloud services across AWS, Google Cloud, or Microsoft Azure.

Requirements:

• Strong experience building cloud architectures and backend systems in Python.
• Hands-on experience with containerization and running containers in production environments.
• Experience orchestrating containerized workloads (e.g., Kubernetes or managed workflow services).
• Proven ability to design abstracted, layered architectures with clear separation of concerns.
• Solid understanding of databases, object storage, data processing patterns (batch/streaming), and API-first design.
• Familiarity with frontend integration needs for map-based or geospatial visualization.

Nice to have:

• Experience with geospatial data formats and services.
• Platform engineering or multi-cloud experience.

Success in this role means that new data sources, processing logic, and APIs can be added quickly through standardized patterns; processing workloads are delivered as self-contained containers; and data products are reliably exposed to frontend applications for map-based visualization.

Location: Remote / Hybrid (as applicable)

Commitment: Contract

Salary Band: $100,000 - $150,000 (Contract)