Preql delivers the data quality and semantic foundation that makes Al agents accurate and trustworthy. Get reliable answers from day one, not after months of prep. Backed by Felicis.
About the role
You will sit inside customer environments, learn how a specific finance organization actually closes its books and plans its year, and build the semantic models that make that work. You will be the person who understands both a customer's GL and our platform internals well enough to get the numbers right and defend them to a controller.
What they're looking for
- 5+ years building with data in production, with deep SQL fluency and comfort in Python
- Direct experience with cloud warehouses (Snowflake, Databricks, BigQuery) and transformation tooling (dbt or equivalent)
- Real working knowledge of financial data. You know why the finance team's definition of revenue is different from the data team's, and you have modeled a chart of accounts, an allocation, or a close process before
- Experience working directly with enterprise customers, including the parts that are uncomfortable: scoping, pushing back, and delivering bad news early
- High tolerance for ambiguity. Early accounts will not have a playbook, and you will write the playbook
- Judgment about when to solve something for one customer and when to solve it for all of them
More about this role
Preql helps enterprises clean, unify, and govern messy internal data so it actually works for AI, analytics, and reporting. We work with large organizations navigating complex data environments and high-stakes operational workflows. Based in New York, our team comes from data infrastructure, AI, and enterprise software.
We’re a small team with little bureaucracy. Leadership expects individuals to take ownership, move quickly, and make good decisions for the company with support from their teammates. The curious do well here, are comfortable operating in ambiguity, and are willing to form opinions and act on their convictions instead of waiting for instructions.
You will sit inside customer environments, learn how a specific finance organization actually closes its books and plans its year, and build the semantic models that make that work. You will be the person who understands both a customer's GL and our platform internals well enough to get the numbers right and defend them to a controller.
This is not a support role and it is not pure services. Every deployment you run should make the next one faster. The work you do by hand in month one should be a product capability by month...
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