About
Where Data Drives Creation
Matthew Burns
Professional headshot
Matthew Burns
Matthew Burns is a data engineering leader and builder with 20+ years of experience shaping how organizations use information to make decisions.
As Director of Data Engineering at Burton Snowboards, Matt led an enterprise Azure/Databricks transformation that cut time-to-insight by 60% and reduced infrastructure costs by 40% — while keeping zero attrition on his team. That work crystallized a conviction that became the studio's foundation: data platforms don't fail because of technology. They fail because organizations don't build the culture to use them.
Burning Studios is where that conviction becomes practice. The studio combines hands-on data architecture expertise — Databricks, Azure, cloud-native lakehouse design — with the organizational strategy that makes data investments actually deliver.
Currently pursuing an MS in AI (Applied AI & Intelligent Systems) to deepen expertise in AI strategy — the next layer for information-driven organizations.
When not in the studio, Matt is hanging out with his wife Jennifer and their 8-year-old son Evan (co-founder of SpaceRace Company and the reason half of the studio's whiteboard is covered in rocket drawings).
Why a Studio?
We call it a studio because that's what it is. A place where things get made.
Too many data transformations follow the same script: hire a consultancy, get a binder full of recommendations, watch nothing change. The recommendations weren't wrong — they just never became real. Nobody built the thing.
Burning Studios exists because the work has to actually get built. We write the code, design the governance, stand up the platforms, and sit with the teams who'll own it all after we leave. The craft is in the making — and the making is what drives business value.
Whether it's an enterprise data lakehouse, a fantasy hockey app, or a kid's rocket t-shirt — if it comes out of the studio, it was built with care.
What We Work With
Data Platforms
Databricks, Azure Synapse, Azure Data Factory, Spark, Delta Lake, dbt
Cloud & Infrastructure
Azure, AWS, Terraform, Docker, CI/CD pipelines
Analytics & Visualization
Power BI, Tableau, self-service analytics design, data catalog tools
Governance & Quality
Governance frameworks, quality monitoring, lineage, compliance
AI & ML
ML pipeline design, AI readiness assessment, LLM integration strategy
Languages
Python, SQL, TypeScript, Spark/PySpark
Studio Principles
The Work Comes First
We're practitioners. The quality of what we build — the platforms, the frameworks, the cultures — is how we earn trust. Not decks. Not frameworks named after Greek gods. The work.
Build Alongside, Not Above
We embed with teams, not above them. Every pipeline, every governance policy, every decision framework is built transparently — with knowledge transfer happening in real time, not in a handoff meeting at the end.
Measure Everything That Matters
We tie every initiative to outcomes the business cares about. Time-to-insight, adoption rates, data quality scores, cost savings. If the work doesn't move a number, we rethink the work.
Leave It Better
The engagement succeeds when the organization doesn't need us. We build for independence — skills, documentation, ownership — so the work sustains and evolves on its own.
Ready to Build Something?
Whether you need a fractional CDO to set direction or hands-on help building the platform and culture, we'd love to talk about the work.
Let's Talk