About BigGeo
BigGeo is the Spatial Cloud.
We help companies manage and access the world’s spatial data.
Any size, any slice, any insight.
Delivered in seconds.
We’re building something that hasn’t existed before: a new layer of the internet where the “where” and “when” behind every decision is instantly clear, programmable, and actionable. Our platform removes the complexity that has kept spatial data locked in silos for decades, and replaces it with speed, precision, and control.
We’re a Calgary-based company, early and moving fast, with real customers, real infrastructure, and a clear point of view on where the world is going.
Why BigGeo Exists and Why People Build Here
Most companies are spatially blind. They know what their data says, but not where or when things actually happen. That gap costs real money, creates real risk, and limits what AI can actually do in the physical world.
BigGeo exists to close that gap.
We’re not building another tool. We’re building the rails that connect the planet’s moving data to the systems that run the world. That’s a big problem, and it takes people who care about doing things right, not just fast.
People build here because:
- The problem is real and the category is open. We’re not competing for the middle of an existing market, we’re defining a new one. Your work shapes what the category becomes.
- Your fingerprints are on the architecture. We’re at the stage where the decisions you make today become the foundation tomorrow. What you ship matters.
- We run on clarity, not politics. We move with purpose. No bureaucratic drag, no HiPPO decisions, just a team that agrees on the mission and gets to work.
- You’ll grow fast because the problems are hard. Spatial data at scale is a genuinely difficult domain. If you want to be stretched, you’ll be stretched.
- We’re building for longevity. We’re not chasing hype cycles. We’re building infrastructure, the kind that compounds in value over time and earns the trust of the companies that depend on it.
The Role
BigGeo is hiring a Spatial Cloud Solutions Architect to help enterprises, partners, and developers design real systems on top of the Spatial Cloud. This role sits at the intersection of platform architecture and real-world implementation. You turn complex spatial data challenges into scalable, production-grade solutions that organizations can run their business on.
You’ll work directly with customer engineering teams, enterprise architects, developer partners, and our internal product and engineering groups. You’ll help organizations move from fragmented spatial workflows, manual GIS stacks, point-to-point pipelines, batch reporting, to unified spatial intelligence systems that power operations, analytics, and AI-driven decision-making in real time.
This is a role for engineers and spatial systems practitioners who like building real things with real customers. You’ll shape how the Spatial Cloud is adopted in the field, and that field feedback loop will directly influence what we build next.
Key Responsibilities
Solution Architecture
- Design Spatial Cloud architectures that integrate spatial datasets, compute systems, and downstream applications.
- Translate customer and partner requirements into scalable, maintainable spatial system designs.
- Develop architecture patterns that hold up under real performance, reliability, and governance demands.
- Produce architecture diagrams, design documents, and decision records that engineering teams can execute against.
Customer and Partner Engagement
- Work directly with enterprise customers implementing spatial intelligence systems on the Spatial Cloud.
- Support developers and partners building products on BigGeo infrastructure, from initial design through production launch.
- Provide technical guidance during onboarding, implementation, scaling, and ongoing optimization.
- Run technical deep-dives, workshops, and design sessions with customer architects and engineering leaders.
Platform Integration
- Design APIs, data pipelines, and integration workflows that connect spatial data to operational systems.
- Ensure solutions use BigGeo infrastructure to deliver high-performance spatial queries and real-time insight.
- Partner with BigGeo engineering teams to improve platform capabilities based on what you see in the field.
Technical Enablement
- Write solution documentation, technical guides, and reference implementations that customers and partners can actually use.
- Build reusable solution patterns that accelerate Spatial Cloud adoption across industries and use cases.
- Create and maintain sample apps, starter kits, and code examples that shorten time-to-first-value.
Cross-Functional Collaboration
- Work with product teams to translate implementation feedback into platform improvements.
- Support go-to-market teams with technical insight for enterprise engagements, technical evaluations, and partner conversations.
- Collaborate with engineering to ensure production reliability of customer deployments.
What You Bring
Required:
- 5+ years of experience working with geospatial systems, spatial data platforms, or location intelligence infrastructure.
- Bachelor’s degree in Computer Science, Geography, or a related field.
- Proven experience designing and deploying spatial data pipelines or geospatial applications in production.
- Strong working knowledge of cloud infrastructure (AWS, GCP, or Azure), APIs, and distributed systems.
- Experience integrating spatial data with enterprise applications, analytics platforms, or AI systems.
- Strong technical communication skills, able to guide both customer engineers and internal teams through complex design decisions.
- Comfort operating in a startup environment: high ownership, tight cross-functional collaboration, fast iteration.
Nice to Have:
- Hands-on experience with GIS platforms, geospatial compute engines, or spatial databases (PostGIS, BigQuery GIS, Snowflake spatial, Esri, H3, S2, or similar).
- Experience designing real-time or high-performance spatial data systems, including streaming spatial pipelines or low-latency spatial query layers.
- Familiarity with developer ecosystems and API-driven platforms: SDK design, developer experience, API versioning, and documentation.
- Experience supporting enterprise implementations of data platforms, including security, governance, and compliance considerations.
- Domain experience in logistics, infrastructure, urban systems, energy, telecommunications, financial services, or climate/earth observation.
- Experience building with AI or machine learning systems that incorporate spatial data, including retrieval pipelines, spatial context for LLMs, or spatially aware agents.
Success Measures
First 30 days:
Full onboarding to the Spatial Cloud platform, internal architecture, and active customer implementations. Shadow active customer engagements and meet the product, engineering, and go-to-market leads you’ll work with most. Produce a first internal architecture review or design write-up that demonstrates command of the platform.
First 60 days:
Own the solution design for at least one active customer or partner implementation. Publish at least one reusable reference architecture, solution blueprint, or integration pattern adopted internally. Establish a recurring feedback loop with product and engineering based on field observations.
