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 Exits 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, 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 seeking a Lead Spatial Cloud Solutions to design and deliver how organizations build, deploy, and scale solutions on the Spatial Cloud.
This role sits at the intersection of platform architecture, spatial systems, and real-world implementation. You will work directly with enterprise customers, partners, and BigGeo’s product and engineering teams to turn complex spatial requirements into production-ready solutions built on BigGeo infrastructure.
You will lead technical solution design across strategic implementations, helping organizations move from fragmented spatial data and workflows to scalable systems that produce operational intelligence. You will define architectures, build reusable technical patterns, guide implementations, and ensure solutions are designed for performance, reliability, governance, and scale.
This is a high-ownership role for a technical builder who combines deep spatial systems knowledge with platform thinking, strong customer engagement, and the ability to move between architecture and implementation.
As Lead Spatial Cloud Solutions, you will own the technical design and delivery of high-impact solutions built on the Spatial Cloud.
You will build and own:
- Spatial Cloud architectures for strategic customer and partner implementations
- Technical solution designs that translate real-world requirements into scalable spatial systems
- Reference architectures and reusable implementation patterns for Spatial Cloud adoption
- Solution blueprints showing how BigGeo integrates with customer data, applications, APIs, and operational systems
- Deployment models for production spatial data and compute workflows
- Technical prototypes and implementations that validate new solution patterns
- Technical guidance across customer and partner implementations
- Feedback loops between real-world implementations and BigGeo’s product and engineering teams
Your work will establish repeatable ways for organizations to build decision-critical systems on the Spatial Cloud.
Key Responsibilities
Spatial Solution Architecture
- Lead the technical design of Spatial Cloud solutions for enterprise customers and strategic partners
- Translate business and operational requirements into scalable spatial architectures, data flows, and compute patterns
- Design solutions that use BigGeo infrastructure effectively across performance, governance, reliability, and scale
- Evaluate spatial datasets, APIs, integration requirements, and existing customer environments
- Make architecture decisions that balance immediate implementation needs with reusable platform patterns
Solution Implementation
- Take solutions from architecture through technical validation and production implementation
- Build prototypes, integrations, data workflows, and reference implementations where needed
- Work through complex spatial data, indexing, compute, and integration challenges
- Identify implementation risks early and develop practical approaches to resolve them
- Ensure solutions can operate reliably under real-world production conditions
Customer and Partner Engagement
- Work directly with technical teams at enterprise customers to understand requirements and guide Spatial Cloud adoption
- Serve as a trusted technical counterpart during solution design and implementation
- Collaborate with data providers, platform partners, and developers building on BigGeo
- Communicate complex spatial architecture clearly to both technical and non-technical stakeholders
- Help customers understand what becomes possible when spatial data can be managed and accessed through a shared infrastructure layer
Platform Enablement
- Create reusable technical patterns, solution frameworks, and reference architectures
- Document deployment approaches that allow successful implementations to be repeated across customers and industries
- Identify common implementation challenges that should become platform capabilities
- Translate implementation experience into actionable product and engineering feedback
- Help establish technical standards for how production solutions are built on the Spatial Cloud
Cross-Functional Collaboration
- Partner closely with engineering teams building Spatial Cloud infrastructure
- Work with product teams to connect customer requirements with platform capabilities
- Collaborate with sales and partnerships during technically complex strategic opportunities
- Contribute spatial systems expertise to product and architecture discussions
- Use AI-assisted tools to accelerate research, analysis, modeling, documentation, prototyping, and solution design
Technology and Tools
The Lead Spatial Cloud Solutions will work across modern spatial, cloud, data, and AI environments.
Relevant technologies may include:
- Cloud platforms and distributed infrastructure
- Geospatial frameworks and spatial databases
- Spatial and temporal datasets
- APIs and developer platforms
- Real-time spatial compute environments
- Data pipelines, transformation systems, and spatial indexing
- Cloud-native application architectures
- AI and machine learning systems using spatial data
- Development and prototyping environments
- Monitoring, debugging, and production reliability tooling
Operational tools include Slack, Google Workspace, and Monday, with strong use of modern AI tools to improve research, technical analysis, development, documentation, and decision-making.
What You Bring
Required Experience
- 7+ years of experience in geospatial systems, spatial platforms, location intelligence, data infrastructure, or related technical environments
- Strong experience designing and delivering production spatial solutions
- Deep understanding of spatial data systems, geospatial compute, spatial indexing, and data pipelines
- Experience designing integrations across APIs, cloud infrastructure, data platforms, and operational systems
- Experience working directly with enterprise customers, technical partners, or complex internal stakeholders
- Ability to translate ambiguous real-world requirements into clear technical architectures and implementation plans
- Strong technical communication skills across engineering, product, customer, and business audiences
- Experience taking technical solutions from initial problem definition through deployment
- Ability to operate with autonomy and make sound technical decisions in a high-ownership startup environment
- Practical experience using modern AI systems to improve technical productivity, analysis, development, or solution design
Preferred Experience
- Experience with cloud-native spatial platforms or large-scale geospatial data infrastructure
- Background in GIS, spatial analytics, spatial databases, or location intelligence systems
- Experience with distributed systems or high-performance data platforms
- Experience designing developer-facing APIs, SDKs, or platform integrations
- Experience supporting developer ecosystems or technical platform adoption
- Experience working with industries such as logistics, infrastructure, energy, government, mobility, or AI
- Familiarity with AI systems that consume or reason over spatial and temporal data
- Experience building reusable solution frameworks, reference architectures, or technical accelerators
- Experience working with large, complex, or real-time spatial datasets
How This Role Contributes to the Spatial Cloud
The Spatial Cloud becomes valuable when organizations can use its infrastructure to build systems that operate against real-world data.
The Lead Spatial Cloud Solutions turns BigGeo’s platform capabilities into working architectures and production implementations.
By solving complex implementation problems and converting those solutions into reusable technical patterns, you will help establish how organizations build on the Spatial Cloud. Your work will connect spatial datasets, compute, APIs, applications, and AI systems into architectures capable of supporting real-world decisions.
Each successful implementation also improves the platform. The patterns you discover, problems you solve, and feedback you bring to product and engineering will help make Spatial Cloud adoption increasingly repeatable.
Your work helps move spatial data from fragmented, specialist workflows into infrastructure that enterprises, developers, systems, and AI can use directly.
Work Environment and Collaboration
BigGeo operates as a collaborative startup environment where teams work closely across engineering, product, data, and customer-facing disciplines.
The Lead Spatial Cloud Solutions will collaborate with:
- Engineering teams building Spatial Cloud infrastructure
- Product leaders defining platform capabilities
- Enterprise customers deploying spatial systems
- Data providers and technology partners participating in the spatial ecosystem
- Sales and partnership teams supporting strategic opportunities
You will have significant autonomy over how technical problems are approached and solved. The role requires initiative, sound judgment, comfort working through ambiguity, and the ability to move between customer requirements, system architecture, and hands-on technical problem solving.
Internal collaboration happens through Slack, Google Workspace, and Monday, with a strong emphasis on transparency, ownership, and AI-enabled productivity.
This role is ideal for someone who enjoys designing complex systems, solving difficult spatial problems, working directly with builders and customers, and turning new infrastructure into capabilities that work in the real world.
Success Metrics
Success in this role means quickly developing the technical and customer context required to independently lead Spatial Cloud solution design, turn implementations into reusable patterns, and create a strong feedback loop between customers and the BigGeo platform.
First 30 Days — Understand the Platform and Establish Technical Context
By the end of your first 30 days, you will:
- Develop a working understanding of the Spatial Cloud architecture, core platform capabilities, spatial data flows, APIs, compute patterns, and deployment environments.
- Understand the active customer and partner solution landscape, including priority implementations, technical requirements, dependencies, and known architecture challenges.
- Build effective working relationships across engineering, product, sales, partnerships, and other teams involved in Spatial Cloud implementations.
- Participate directly in customer and partner technical discussions and demonstrate the ability to translate requirements into clear technical problems and architecture considerations.
- Review existing solution architectures and identify initial opportunities for reusable patterns, improved documentation, or technical standardization.
- Establish an AI-enabled working approach for research, architecture analysis, prototyping, documentation, and technical decision-making.
First 60 Days — Own Solutions and Establish Repeatable Patterns
By the end of your first 60 days, you will:
- Independently lead the technical architecture of at least one strategic customer or partner solution from requirements through an agreed implementation design.
- Translate complex spatial requirements into clear architectures covering data, compute, APIs, integrations, deployment, performance, and reliability.
- Produce or materially improve at least one reusable reference architecture, solution blueprint, implementation pattern, or deployment guide based on real-world implementation experience.
- Demonstrate effective technical leadership in customer conversations, including identifying architecture risks, resolving ambiguity, and guiding technical decisions.
- Establish a clear mechanism for bringing recurring customer and implementation insights back to product and engineering.
- Identify common technical friction points that could be addressed through platform improvements, tooling, documentation, or standardized solution patterns.
- Use AI-assisted workflows to measurably accelerate technical research, prototyping, analysis, or documentation while maintaining technical quality and judgment.
First 90 Days — Deliver, Scale, and Influence the Platform
By the end of your first 90 days, you will:
- Own multiple strategic Spatial Cloud solution engagements or implementations with clear technical direction, documented architectures, and defined paths to production.
- Deliver or materially advance at least one solution toward production use, demonstrating that its architecture meets the required performance, reliability, governance, and scale expectations.
- Establish a reusable set of solution patterns or reference architectures that reduces the effort required to design subsequent Spatial Cloud implementations.
- Demonstrate a repeatable approach for moving from customer requirements to architecture, technical validation, implementation, and production readiness.
- Provide product and engineering teams with prioritized, evidence-based feedback derived from real customer implementations.
- Identify where recurring solution requirements should become native platform capabilities rather than repeated implementation work.
- Become a trusted technical leader across customer, product, and engineering discussions involving Spatial Cloud architecture and adoption.
- Demonstrate that successful implementations are creating leverage beyond individual customers by improving documentation, technical patterns, platform capabilities, or future deployment speed.