# Data Platform Engineer at Monaco

Data Platform Engineer at Monaco in San Francisco. On-site, full-time, paying $200k–$400k. Posted February 10, 2026.

- Company: Monaco
- Location: San Francisco
- Workplace: On-site
- Job type: Full-time
- Pay: $200k–$400k
- Experience: 5+ years
- Posted: 2026-02-10
- Apply: https://jobs.ashbyhq.com/monaco/e2e315e4-c024-4d88-8cdb-11690a6a08e0/application
- Source: https://jobmagic.ai/jobs/data-platform-engineer-monaco-wkbmww

## Requirements

- 5+ years building data platforms, ML infrastructure, or backend systems.
- Deep experience in technologies like PostgreSQL, Redis, Celery, Temporal, ElasticSearch or Turbopuffer, Kafka, Spark, Databricks or Snowflake, etc.
- Ability to lead major architecture decisions and execute on them fast, maintain and scale production systems through rapid workload growth.

## Description

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.

### **The Role**

We're looking for a Data Platform Engineer to help build Monaco's data and ML platform - the pipelines, context systems, and infrastructure that power our AI-driven product. You'll work on the foundation that makes models, agents, and workflows actually useful in production.
This is a high-ownership role at the intersection of data engineering, distributed systems, and applied AI.

### **What You'll Do**

- Build scalable pipelines and event-driven systems for ingesting, transforming, and serving data.

- Support ML workflows: training data, evaluation, embeddings, feature pipelines.

- Solve distributed systems challenges around reliability, latency, consistency, and scale.

- Improve observability, tooling, and developer experience for data, ML, and agent systems.

### **What You'll Bring**

- 5+ years building data platforms, ML infrastructure, or backend systems.

- Deep experience in technologies like PostgreSQL, Redis, Celery, Temporal, ElasticSearch or Turbopuffer, Kafka, Spark, Databricks or Snowflake, etc.

- Ability to lead major architecture decisions and execute on them fast, maintain and scale production systems through rapid workload growth.

### **Location**

- San Francisco. We're an in-person team - 5 days in the office. At this stage, proximity genuinely accelerates product quality and team cohesion.