Translate Complexity: Act as the ultimate bridge. Translate messy customer business problems into precise technical specs, transformation logic, and data requirements for our engineers and data scientists.
Own the GTM: Collaborate with Product Marketing and Sales to launch features that aren't just technically impressive, but actually move the needle on SaaS metrics (Adoption, Retention, ARR expansion).
Hypothesize & Validate: Use your analytical skills to dive into data assets, validate assumptions, and prove (or disprove) product hypotheses before writing code.
What You’ll Bring to the Table
3+ years of relevant experience across Product Management, Data Analytics, or Data Engineering.
Strong Business & Product Acumen: The ability to look at a complex technical feature and immediately see how it connects to customer ROI.
SQL Fluency: You are comfortable writing joins and aggregations to explore data yourself. (We care about your analytical problem-solving, not whether you memorized advanced syntax).
Data Visualization Chops: Experience with a modern BI platform (e.g., Sigma, Tableau, Looker) and a strong sense of how to present data clearly.
- The "Translator" Superpower: Elite communication skills. You can pitch a vision to an executive client, align a sales team, and debate data modeling with an engineer.
- WHO YOU ARE:
- Great product minds don’t all follow the same blueprint. You likely fall into one of these buckets:
The Seasoned Data PM: You already build data products but want a more visible, customer-facing role where you can co-develop directly with clients on a modern stack.
The Data-Obsessed SaaS PM: You manage a standard SaaS product, but you secretly spend all your time in SQL, building dashboards, and lurking in the analytics team's Slack channels. You're ready to make Data/AI your full-time focus.
The Product-Minded Analyst: You're a Senior Data Analyst or BI Developer who doesn't just answer "what happened?" but actively tells stakeholders "what's next." You’ve been "unofficially" product-managing your work for a while and are ready to make it official. WHAT YOU'LL BRING: 3+ years of relevant experience across Product Management, Data Analytics, or Data Engineering.
Strong Business & Product Acumen: The ability to look at a complex technical feature and immediately see how it connects to customer ROI.
SQL Fluency: You are comfortable writing joins and aggregations to explore data yourself. (We care about your analytical problem-solving, not whether you memorized advanced syntax).
Data Visualization Chops: Experience with a modern BI platform (e.g., Sigma, Tableau, Looker) and a strong sense of how to present data clearly.
- The "Translator" Superpower: Elite communication skills. You can pitch a vision to an executive client, align a sales team, and debate data modeling with an engineer.
- WHAT WOULD ALSO BE AWESOME:
- Our Stack: Experience with (or a burning desire to learn) our modern data stack: Snowflake, DBT, Fivetran, and Sigma.
Industry Context: Experience in complex B2B SaaS verticals—especially physical operations like Field Services (logistics, routing, dispatch) or Building Services—is a massive plus. These industries are sitting on massive, unoptimized datasets ripe for AI disruption.
Coding Lite: Familiarity with Python or R for lightweight data analysis.
AI/ML Exposure: Experience working around the machine learning lifecycle or productionized models.
