RevQL
Founder
Architecting an open-source revenue recognition workbench, deterministic ASC 606 calculation engines, and code-first data engineering pipelines for mid-market finance teams.
Data Engineer & Founder building RevQL
I am the founder of RevQL, an open-source, accountant-in-the-loop revenue recognition workbench and pipeline layer. It provides mid-market finance teams with an audit-ready review interface and deterministic ASC 606 calculation engine without requiring an ERP overhaul.
RevQL pairs an open-source core (OpenRevRec) for single-tenant or on-premise execution with managed hosting and code-first data engineering services to connect messy CRM, CPQ, and billing feeds directly to existing accounting ledgers.
We are currently establishing design partnerships with finance teams running hybrid or complex recurring contracts on QuickBooks, Xero, or entry NetSuite.
Learn more about RevQL →In 2023, I worked as a solutions engineer at Klarity AI building enterprise integrations for automated contract accounting. The work made two realities obvious: first, that messy contract intake combined with the data plumbing behind it is the true operational bottleneck; and second, that accounting controls require deterministic execution and unambiguous audit trails, not black-box generative text.
The experience left such an impression on me that I went on to complete a formal degree in accounting. When Klarity pivoted upstream to pursue broader enterprise digital transformation, the mid-market wedge was vacated. Mid-market companies with messy, heterogeneous contracts remain caught between simple tools that assume straightforward, standardized terms, and six-figure enterprise ERP modules.
I have kept a close eye on this space ever since, waiting for the underlying technical pieces to mature. Recent advancements have finally converged to make a lightweight, code-first architecture viable:
Small language models can now extract complex contract clauses with reliable citations directly into structured schemas. Compact open-weight reasoning models can run locally or in private VPCs with near-zero marginal inference cost. Combined with code-first pipeline tooling like dlt, dbt, and Dagster, we can now replace bespoke iPaaS connectors with auditable, version-controlled transformations.
With an accounting foundation and years spent architecting data warehouses and integration pipelines, this convergence aligns directly with the problems I know how to solve.
Founder
Architecting an open-source revenue recognition workbench, deterministic ASC 606 calculation engines, and code-first data engineering pipelines for mid-market finance teams.
Founder & Technical Lead
Built data-intensive products and developer infrastructure end to end, including DuckDB-backed services, analytical APIs, multi-tenant application systems, and production observability.
Senior Analytics Engineer
Developed dbt models in Snowflake and customer-health logic that gave Scaled Customer Success visibility into roughly 40% of managed revenue exposed to churn risk. Connected those signals to operational workflows across thousands of accounts.
Solutions Engineer
Turned complex enterprise data integrations into repeatable Python tooling and ingestion patterns for contract extraction and revenue accounting workflows, automating 70% of manual integration effort.
Senior Analytics Engineer
Built event-driven reporting and data-quality workflows with dbt, Snowflake, Airflow, Python, and the Looker API. Write-Audit-Publish controls reduced downstream reporting errors from stale refreshes by 85%.
Analytics Engineer, Marketplace Demand Lead
Led reporting strategy and self-service BI rollout for more than 70 stakeholders. Refactored investor reporting into modular dbt models, reducing monthly generation time by 90%.
Founding Data Engineer
Joined as the first data hire and built the modern data stack for a 40-person Series A company, covering executive reporting, finance, inventory, customer cohorts, and operational analysis.