Geospatial Solution Architect
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Job Description
Geospatial Solution Architect designing and delivering GIS solutions for Alberta’s Ministry of Technology & Innovation. Lead integration across enterprise applications, focusing on spatial data and AI-enabled operations.
Responsibilities:
- Design and deliver integrated GIS solutions across enterprise applications, APIs, and data platforms
- Develop full-stack custom geospatial applications and services where needed
- Architect and implement spatial data flows, integrations, and pipelines across systems
- Select and apply appropriate technologies based on solution needs
- Produce clear, implementation-ready solution designs and technical documentation
- Lead technical delivery, provide design oversight, and mentor team members
- Implement secure, scalable, and reliable solution architectures
- Build and maintain automated deployment pipelines and testing practices
- Evaluate emerging technologies and contribute to platform and architectural evolution
- Identify and remediate technical debt while ensuring continuity of service
- AI is a key enabler in this role, practical experience applying AI is critical.
Requirements:
- University graduation in Computer Science, Information Technology or a related field.
- Minimum of 4 years of experience in geospatial platform architecture.
- Minimum of 4 years of experience in software development & engineering.
- Minimum of 4 years of experience in spatial data pipelines & integration.
- Minimum of 4 years of experience in SDLC & DevOps automation.
- Minimum of 4 years of experience in technical leadership & cross-team coordination.
- Minimum of 4 years of experience in production support & service operations.
- Minimum of 4 years of experience in security, reliability & disaster recovery.
- Minimum of 4 years of experience in AI-enabled operations.
- Experience building responsive, accessible spatial web applications.
- Experience developing mobile or field spatial solutions.
- Experience building AI-powered geospatial features.
- Knowledge of ML-driven spatial analysis.
- Solid understanding of responsible AI practices.
- Experience in production-grade deployment and tuning of open-source geospatial tools.
- Experience in enterprise spatial database administration and performance tuning.
- Experience in producing technical documentation.
- Experience in technology economics.
- Experience in communicating technical concepts to diverse audiences. Certification (any of the following):
- AI or Machine Learning certification.
- Esri Technical Certification.
- FME Certified Professional.
- TOGAF 9 Foundation or Professional.
- Certified Geographic Information Professional (GISP) or equivalent credential.
Benefits:
- Positive workplace culture and work-life balance
- Leadership and mentorship programs
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