Data & Product Engineer - Fintech

We're setting new standards in corporate finance. With a focused team of 30 — one in four of us a former founder — we combine deep expertise in finance, data science and AI to build
THE
platform for deal & advisory teams, strategy departments, auditors and banks. We're one of the fastest-growing startups in the DACH-region and now scaling internationally. Our ambition is clear: to set the global standard.

• Ownership.You own your topics end to end, from idea to shipped.
• Strong opinions, loosely held.We argue hard about the right solution, then commit together.
• Simple beats clever.The simplest thing that solves the problem wins. We'd rather ship clear code than impressive code.
• Leave it better than you found it.Speed is a priority, but we don't trade it for technical debt that kills future velocity. We build simple, modular systems that are easy for the next person (or future you) to understand.
• Mistakes are a gift.We make mistakes and learn from them. The one thing we avoid is making the same one twice.
• Serious about the work, not about ourselves.We take our goals seriously, ourselves less so.

Small team, high bar. You'll own the data our platform runs on — finding new sources, getting them into production, and building the features that make them useful to corporate finance teams. Over six months you'll work on the same codebase and the same roadmap as the rest of the engineering team. Your responsibilities will include:

• Research and evaluate new data sources
  : company registers, filings, industry databases and the open web.
• Build and maintain Python integrations that bring those sources into production reliably.
• Develop LLM-powered pipelines that extract structured data from PDFs, filings and free text.
• Design and ship end-to-end features that turn new data into something deal teams can work with.
• Take ownership of data quality through validation, monitoring and automated checks.

to be successful in this role, you will need:

• We expect the motivation and ownership of a founder. You own problems end-to-end and care more about the user outcome than your ticket description.
• Degree in CS, Data Science, Mathematics, Physics or Engineering, completed or in progress, or equivalent practical experience.
• Proficiency in Python
  . You can handle messy real-world data and build the APIs and services your features rely on.
• Comfortable working with third-party data sources
  : authentication, pagination, rate limits, JSON/XML/CSV, plus parsing or scraping when there is no API.
• Hands‑on experience with databases such as PostgreSQL.
• Experience handling large, complex datasets
  , whether from a project, a thesis or your own work.
• You use AI/LLM tools to move faster, but you have the technical depth to audit their output and maintain high code quality. No "AI slop".
• Strong communication and structured problem-solving skills.
• Available full‑time for 6 months
  , based in or moving to Munich (hybrid).

• You've worked with financial or company data
  : filings, registers, market or transaction data.
• Experience with big data technologies (e.g. Apache Spark, Kafka) &
  data orchestration tools (e.g. Dagster, Airflow).
• You've used LLMs to extract structured data from unstructured documents.
• A background or interest in finance, M&A or capital markets
  .
• Own projects
  : a scraper, a dataset, a tool you built for yourself.

• Responsibility from day one
  : flat hierarchies, fast decisions, and the room to actually shape the product.
• Permanent Employment: strong interns are the first people we talk to about a full-time role.
• Learning curve:one of the steepest you’ll find in Germany. Not an empty claim — ask the team.
• People:Build with experts from Big Tech, Silicon Valley, Investment Banking, and Hedge Funds.
• Setup:Munich, hybrid. Modern office, EGYM Wellpass, team events, tax‑free benefits.
• Relocation:company apartment in Munich available on request.

English is our company language;
German is nice to have
.

We’re an equal‑opportunity employer. This role is open to all genders (m/f/x). We value diverse backgrounds and perspectives and welcome applications from all qualified candidates.