Building tools that surface hidden value.
In careers, markets, and games.
Wesley Johnson
Founder & Engineer
Wesley Johnson brings 8+ years of experience spanning data engineering, product management, and full-stack development. Before founding DataViking in January 2026, Wesley served as Senior Manager at Peloton, where he led data-driven product initiatives at scale. Prior to that, he built analytics and automation systems at Brinks Home, solving real operational problems with data infrastructure.
Wesley holds a degree from Kansas State University and has developed a bench of 71 professional skills across data science, machine learning, software engineering, and product strategy. The thread connecting every DataViking product is the same: find the signal that's already there but nobody's surfaced yet. Traitprint does it for careers, mapping real skills to real jobs. The MTG Data Platform does it for collectible markets, turning raw pricing data into actionable trade signals. The Living Stone does it for game worlds, using procedural generation to create environments that feel discovered rather than designed.
His background spans the full stack — Python and Go on the backend, TypeScript on the frontend, Unreal Engine and Godot for game development, and a deep bench in ML/AI tooling (PyTorch, LLM orchestration, vector search). But the common denominator isn't any particular language or framework. It's the conviction that the best tools are the ones that show you something you couldn't see before.
Data Engineering
- Pipeline architecture
- ETL/ELT at scale
- Data quality systems
- Warehouse design
AI & Machine Learning
- ML model development
- LLM orchestration
- NLP & embeddings
- Recommendation systems
Game Development
- Unreal Engine & Godot
- Procedural generation
- Multiplayer systems
- Game design
Mission
Building tools that surface hidden value — in careers, markets, and games.
Careers
Your real skills are buried in years of experience nobody reads. Traitprint maps what you can actually do to roles that actually fit.
Markets
Collectible markets generate enormous data that's mostly noise. We build the signal layer that turns pricing chaos into trading clarity.
Games
The best game worlds feel discovered, not designed. Procedural systems create emergent experiences that surprise even their creators.
Technical Philosophy
How we think about building software.
Ship, then polish
Working software beats perfect plans. We ship early, learn from real usage, and iterate. Every DataViking product started as a rough prototype that solved one problem well.
Data is the product
UI is how you deliver insights, but the insights come from the data layer. We invest disproportionately in data pipelines, ML models, and scoring algorithms — the parts users never see but always feel.
Own the full stack
When one person understands the pipeline, the model, the API, and the frontend, decisions compound instead of getting lost in handoffs. Small teams with full-stack ownership move faster than large teams with narrow roles.
Agents as teammates
AI agents aren't just a product category — they're how we build. From automated code review to synthetic user research, we treat AI as a force multiplier for a small team doing ambitious work.