Email marketing and sales-page builder with AI-powered content and automations
Flodesk is a 51–200-person marketing software company built on a Python/Go/Node stack that processes 1B+ monthly events through Apache Airflow, Dagster, dbt, and Redshift. The tech mix—heavy data pipeline orchestration layered over real-time Kinesis streams—reveals infrastructure investment far beyond typical email-marketing SaaS, likely driven by billing complexity and at-scale automation demands. Engineering-led hiring (4/5 recent roles) focused on senior and lead profiles signals infrastructure and backend scaling is the core bottleneck.
Flodesk is a self-serve marketing platform for entrepreneurs and small businesses, combining email design and sending, sales-page builders, payment processing, and email automation in a single interface. The product integrates with Shopify, WooCommerce, and Zapier to fit into existing merchant workflows. Internally, the company runs a sophisticated data platform (Airflow, Dagster, dbt, Redshift, Kinesis) that underpins billing, automation triggers, and compliance—reflecting the operational complexity of processing recurring charges and user-triggered workflows at scale. Based in San Francisco, the company was founded in 2018 and operates with a 51–200-person team, currently hiring across US and Vietnam offices.
Python, Go, Node.js, React, PostgreSQL, AWS (Redshift, Kinesis, Glue), Apache Airflow, Dagster, dbt for the backend and data platform. Frontend uses TypeScript, React, and Vite. Integrations layer includes Shopify, WooCommerce, Zapier.
51–200 employees, based in San Francisco, California, with hiring activity in Vietnam and the United States.
Flodesk's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.