Senior Growth Product Manager - Soda

Data quality is the bottleneck of the AI era. Soda is the data quality layer for companies like Disney, Ralph Lauren, CBRE, HelloFresh, 2K Games, and Nubank. Our open-source engine, Soda Core, is used by companies like Tesla, Slack, Adyen, Walmart, and JPMC.

We are hiring a Senior Growth Product Manager to get customers using Soda faster and across more of their data.

About Us

Soda's mission is to monitor the world's decisions. We're building the first Data & AI performance monitoring platform that spans data collection to automated decision-making. Soda helps customers find, understand, and fix data quality issues by combining automated post-production monitoring with pre-production pipeline data testing.

Soda was founded in 2019 by Maarten (employee #5 at Collibra) and Tom (creator of multiple open-source projects generating hundreds of millions in value). We commercialize through Soda Cloud and we're well-funded, with investors like Point 9 Capital, Hummingbird, Singular, and Eurazeo.

The Role

You'll lead our adoption team—a small group of frontend, full-stack, and AI engineers. The team works on onboarding and activation, keeping workflows coherent across the product, customer-facing dashboards, and AI features that save users work.

Most of our roadmap is driven by what customers and prospects ask for. This team's work is driven by adoption metrics. You'll start from a hypothesis, ship changes, and evaluate the results.

We sell to enterprises, so sample sizes are small and A/B tests rarely reach statistical significance. You'll use product analytics, session replays, and conversations with users to decide with incomplete data.

What You'll Do

• Own adoption metrics for Soda Cloud: Time to first verified contract for new accounts, data coverage, weekly active datasets and users, and AI feature usage.
• Own workflow UX: Keep workflows coherent for data engineers and business users (data stewards and governance leads).
• Identify friction points: Find where customers get stuck between contract signing and deployment across their data.
• Design onboarding flows: Get new teams to first value within days, including self-serve paths for technical evaluations.
• Leverage AI for adoption: Identify tasks suitable for AI agents, ship features, and evaluate usage retention.
• Collaborate cross-functionally: Work with Growth on launches and product marketing, and with customer engineers on deployment blockers.

Hiring Process

1. Application: CV and a short description of a metric you moved (starting point, outcome, what shipped, what failed).
2. 15-minute Phone Screen
3. First Interview (60 min): Deep dive into past growth work, including a demo of something you shipped.
4. Second Interview (60 min): Working session on a real Soda adoption problem.
5. Culture Fit (45 min)

Requirements

You Should Have

• 5+ years in product (with at least 2 years owning growth, activation, onboarding, or adoption in B2B SaaS).
• Product craft and UX taste: Strong product intuition, small scope iteration, direct customer interview experience, and clear UX opinions.
• AI-native approach: Experience shipping AI-powered features, prototyping with coding agents (Claude Code, Codex, etc.), and making small PRs.
• Hands-on analytics skills: Proficiency in writing SQL, building funnels, and working with small sample sizes.
• Technical product experience: Familiarity with data pipelines, data warehouses, and APIs.
• Strong written communication: Comfort working asynchronously across a distributed team (in English).

Good to Have

• Experience in data quality, data observability, data governance, or data infrastructure.
• Product-led growth (PLG) experience within an enterprise sales environment.
• Experience with Shape Up or fixed-time, variable-scope frameworks.

What We Offer

• Compensation: €120,000–€140,000/year + equity.
• Work Setup: Fully remote within Europe (contractor position outside Belgium; Belgian office available if desired).
• Team Offsites: Bi-monthly 3-day in-person kickoffs in Europe with the product and engineering team.
• AI Tools: Unlimited API access/tokens across frontier models.
• Flexibility: Remote work with flexible working hours.