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Farseer logo

Product Modeling Engineer

Farseer
Posted May 27, 2026, 10:45 PM UTC
🌍Europe🏢Hybrid📁Engineering & Development
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Farseer is a fast-growing startup building an enterprise software stack from first principles. We aim to become the underlying database and operating system for every business-critical app, from financial planning and analytics to accounting and beyond. Farseer empowers humans to build enterprise software with the help of AI. Over the next decade, we will rebuild the enterprise nervous system. We are starting with finance, a real-time collaborative planning and reporting platform that turns finance teams into proactive strategists. Once that foundation is solid, the same AI-native core will extend across the operational stack, reporting, supply chain management, manufacturing, procurement, revenue ops, and more. Our mission is to build enterprise software that people enjoy using. No user-hostile screens. No bloated workflows. Just fast, intuitive tools that help teams solve real business problems. Build the modeling brain of modern finance. At Farseer, we're building an Enterprise Operating System for finance teams — powered by our own high-performance analytical engine. Our customers don't just use dashboards. They build multidimensional financial models with variables, dimensions, hierarchies, rollups, and calculated logic. When something is wrong, slow, or unclear — it's rarely a bug. It's a modeling problem. We're looking for a Product Modeling Engineer to own that layer. This is not helpdesk support. This is structured thinking, abstraction, and product leverage. What You’ll Actually Do You will work at the intersection of: Data modeling Financial logic Multidimensional structures Product architecture Your work will include: Translating business descriptions into structured models (variables, dimensions, hierarchies) Debugging aggregations, rollups, grain issues, and double-counting across customer tenants Identifying modeling anti-patterns and proactively improving customer models Influencing product roadmap based on real-world edge cases Building reusable modeling patterns and playbooks Using AI tools (Claude Code, Codex) to prototype, analyze, and automate modeling workflows You will see how dozens of companies structure their financial logic, and shape how our product evolves. This Role Is For You If You enjoy: Turning paragraphs into schemas Designing clean data structures Finding where logic breaks Reasoning about relationships and cardinality Thinking in systems You might have worked as: Analytics Engineer or BI Engineer Data Modeler or ERP/Planning Implementation Consultant Software Engineer with strong data modeling interest Quantitatively strong finance professional who loves structure What Matters Most We care far more about structured thinking than specific background. You should be comfortable with: Abstraction Data modeling concepts (fact vs dimension, grain, joins) SQL or similar querying language Explaining complex concepts simply Using AI tools productively as part of your daily workflow Nice to have: Experience with BI or planning tools Financial modeling exposure Experience with semantic layers SaaS product environment You do not need to be a finance expert. You do need to think clearly and structurally. Why This Role Is Different This is not reactive ticket resolution - you're part of the product brain. You will: Influence product roadmap based on real modeling patterns you see across customers Work directly with Engineering to improve how dimensions, variables, and rollups behave Build reusable modeling frameworks that scale across tenants Shape how enterprise teams think about financial structure What We Value At Farseer, we value agency over waiting and outcomes over tasks. If you see something broken, you fix it. If a model is flawed, you improve it. If abstraction can be cleaner, you propose it. If you want to own turning messy business logic into clean, scalable models that power enterprise decisions, apply now. Let's build the modeling engine that turns financial complexity into clarity.

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