Boston, MA · Open to senior BI & analytics engineering roles
I build trusted data models, metrics, and reporting systems that turn messy operational data into decisions.
Analytics lifecycle
Definition, lineage, and validation are part of the product—not cleanup after the report ships.
Selected work
Three examples of owning the path from ambiguous operational data to governed analytics systems. Names and sensitive details remain intentionally limited.
Replaced a hand-built executive workbook with a governed dbt semantic layer, giving Finance, Operations, and leadership one definition of recruiter headcount.
Outcome: Every downstream report now uses the same definition.
Took a canonical library of 50+ company metrics into the warehouse and built point-in-time history for reproducible period reporting.
Outcome: Executive reporting now runs on governed views.
Defined and modeled the validated outcomes behind product-performance reporting, with shared rules across Product, Engineering, and Finance.
Outcome: A validated fact table ready for product reporting.
Experience
Seven years progressing from client data systems and revenue analytics to governed metric layers, warehouse architecture, and executive decision support.
Download the full résumé →Client systemsBI developmentAnalytics engineeringData ownership
Owned executive reporting, governed metric delivery, and warehouse automation.
Connected geospatial, lease, asset, and market data for portfolio decisions.
Built durable revenue datasets and reporting for multiple business units.
How I work
Business question → metric definition → warehouse logic → QA → BI experience. Each step makes the next one more reliable.
Write the metric contract: owner, grain, rules, and the decision it supports.
Make reusable logic versioned, reviewable, and available beyond one report.
Use source parity, structural checks, and stakeholder review before release.
Expose a governed answer where people make decisions.
Independent projects
A small collection of work that demonstrates techniques and questions I cannot show from client systems.
About
I studied geography at UMass Amherst, and I still approach data the way a cartographer approaches a map: it should be accurate, honest about what it leaves out, and readable by someone who was not in the room.
My work moved from client data implementations to revenue analytics, geospatial systems, and analytics engineering. The common thread is understanding complicated systems and making them understandable enough to act on.
I use AI coding tools to move faster, and I verify every result before it ships.
B.A. Geography (Globalization & International Studies) · GIS Certificate · UMass Amherst, 2018
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