San Francisco, California, United States
Onsite
Monaco is building an AI-native revenue platform that replaces the fragmented GTM stack - CRM, sequencing, call recording, enrichment, pipeline management with one unified system, consolidating 6–10 disconnected tools into a single platform built for the AI era.
We launched publicly in Feb 2026, are already 65 people, and have strong early product-market fit generating millions in ARR within months of launch. You'll have the chance to both scale our core systems and build new features from 0 to 1.
We've raised $85M in our Series B from Founders Fund, Benchmark, and Human Capital, and our founders previously led Brex, Apollo, and Clari.
Come join us if you want to be part of a high autonomy, high pace team reinventing one of the biggest categories in enterprise software.
We're looking for a Technical Lead to own the technical direction of Monaco's Data Ingestion Team. You'll drive data infrastructure, analytics, and insights that power how our customers and internal teams make decisions. This is a hands-on role, you'll be in the code every day but we're looking for someone who's led before and knows how to set technical direction, raise the bar, and make the people around them better.
Own the architecture and execution of our company and contact data pipeline.
Define and drive data ingestion initiatives end to end, from scoping to delivery.
Set the technical standard for how we work with data: tooling choices, modeling practices, and documentation.
Partner closely with product, engineering, and go-to-market teams and external vendors to turn data into leverage.
Prior experience as a tech lead or equivalent - you've set technical direction and owned outcomes, not just executed tasks.
Strong SQL and data modeling skills; comfortable owning a dbt project end to end.
Experience with modern data warehouses (Databricks, Snowflake, BigQuery, Redshift, etc.).
Python proficiency for analysis and automation.
Clear technical communicator who can align stakeholders and cut through ambiguity in a fast paced environment.
Experience with working with GTM or revenue data.
Experience with learning, maintaining and cleaning large scale data patterns.
San Francisco. We're an in-person team - 5 days in the office. At this stage, proximity genuinely accelerates product quality and team cohesion.
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