Middle to Senior Data Analyst

<div class="content-intro"><p>Flodesk is recognized in the Inc 5000 as one of the world's fastest-growing email marketing companies, built to help entrepreneurs sell online and design emails that people love to get. We're committed to giving small businesses simple and intuitive tools that help them grow, nurture, and monetize their email list.</p> <p>We’re a remote-first company headquartered in San Francisco with a globally distributed team, including in-person hubs in Da Nang (Vietnam), Barcelona (Spain), and Menlo Park (California). Our team reflects the diversity and creativity of the people we serve. Join our mission to level the playing field for small business owners through good design.</p></div><h3><strong>About The Opportunity</strong></h3> <p>The Data Team at Flodesk is part of our Engineering Team, based in our Da Nang office. We serve as the single source of truth for the company, providing data-driven insights that empower teams across Product, Marketing, Finance, and Engineering.&nbsp;</p> <p>As a Data Analyst, you’ll play a crucial role in translating raw data into meaningful insights, optimizing data pipelines, and maintaining a self-service BI ecosystem that enables teams to explore and understand data effectively.</p> <p><strong>What you will do</strong></p> <ul> <li><strong>Data modeling and analysis:</strong> Own the dbt models and analysis behind Flodesk’s business metrics, taking raw data to tested numbers that every report agrees on. Build automated checks that reconcile data across sources, and trace any gap down to the rows behind it. Most of your work will sit in the finance domain (MRR, retention, LTV/CAC, and revenue and cost reconciliation), so prior knowledge of SaaS metrics and subscription billing models will help.</li> <li><strong>Business partnership: </strong>Be the data partner for our business team, mostly the Finance Director and leadership. Turn their questions into well-defined metrics, help settle open definitions (say, how to count a member who converts and cancels in the same month), and build the decisions into the models.</li> <li><strong>AI-first analytics:</strong> Do most of your building and analysis through AI agents, and own the result: checking the logic, testing edge cases, and catching what the agent got wrong. You’ll build the dashboards using AI agents and curate the metric definitions and metadata that keep MCP answers accurate.</li> </ul> <h3><strong>What you need to be successful</strong></h3> <ul> <li>2+ years as a data analyst or analytics engineer, working hands-on in SQL against a production data warehouse.</li> <li>Advanced SQL and data modeling. You pick the right grain for each table and get snapshot and point-in-time logi