Senior Data Platform Engineer - AI-Driven Fintech

Monk; San Francisco (CA); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

Health & dental

Equity

Job summary

Monk is seeking its first dedicated data hire in Flatiron, NYC to own the data platform end to end—ingestion, transformation, storage, and serving—creating a single source of truth for AI agents and customers.

You will design scalable data infrastructure, enforce data quality, and build data products for AR health and cash flow insights. Requires 4+ years building production data systems with Postgres/SQL and cloud infrastructure.

Qualifications

• 4+ years building production data systems at a venture-backed startup.
• Expert in Postgres and SQL.
• Hands-on with Supabase, AWS, Vercel, or comparable modern cloud infrastructure.
• Owner mindset: you fix failures and prevent recurrences.
• AI-native: you use AI to move faster and build production-grade data foundations.

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.

Skills

Postgres

SQL

Data pipelines

ETL/ELT

Event-driven

Tools

Supabase

AWS

Vercel

Job description

Monk is seeking its first dedicated data hire in Flatiron, NYC to own the data platform end to end—ingestion, transformation, storage, and serving—creating a single source of truth for AI agents and customers.

You will design scalable data infrastructure, enforce data quality, and build data products for AR health and cash flow insights. Requires 4+ years building production data systems with Postgres/SQL and cloud infrastructure.