Member of Technical Staff: Data

Monk•San Francisco, CA

1d•Onsite

About The Position

Monk is an AI-native accounts receivable platform for B2B companies. We automate billing, collections, and payments so finance teams can turn outstanding invoices into cash, faster. We believe the AR stack is broken and the finance function deserves much better. We are bringing AI, speed, and real craftsmanship to a space that has been ignored for too long. You will be Monk's first dedicated data hire. Money movement runs on data, and ours has to be correct every time. You will own the pipelines that ingest, normalize, and reconcile financial data across every customer environment and the data foundation our AI agents reason over. This is not a supporting role. You will set the architecture, own the quality bar, and build the platform we scale on.

Requirements

4+ years building production data systems at a venture-backed startup. You joined when the data layer was duct tape, scaled it through real growth, and lived with the consequences of your own architecture
Expert in Postgres and SQL. Deep experience with data pipelines, ETL/ELT, and event-driven processing
Hands-on with Supabase, AWS, Vercel, or comparable modern cloud infrastructure
Owner. You do not file tickets about pipeline failures. You fix them, then make sure they cannot happen again
AI-native. You use AI to move faster and you are excited to build the data foundation that makes AI agents production-grade
In-person in Flatiron, NYC

Nice To Haves

fintech or payments data systems
data infrastructure for LLM or agent products
founding or early data hire

Responsibilities

Own Monk's data platform end to end: ingestion, transformation, storage, and serving
Design and build the data infrastructure that turns messy customer data into a single source of truth for agents and customers.
Own data quality and correctness end to end and do not accept “mostly right” as an answer. Build best-in-class monitoring, validation, and alerting for your work.
Build customer-facing data products: visibility into AR health, agent behavior, and cash flow that customers can act on
Make data easy to debug, easy to query, and fast at 10x and 100x today's volume