Founding Data Engineer (Spark/Python/Elastic) at Fintool (W23)
$135K - $300K  •  
Financial copilot for institutional investors
San Francisco, CA, US
3+ years
About Fintool
About the role
Skills: Machine learning, Spark, Deep Learning, Python

Apply here


Fintool is a financial copilot for institutional investors. It’s ChatGPT on top of financial documents, starting with SEC filings. Fintool is engineered to discover financial insights beyond the reach of timely human analysis or search software. It helps from summarizing long 10-K to finding new investment opportunities.

Fintool is backed by Y Combinator as well as entrepreneurs such as the co-founders of Datadog, Vercel, HuggingFace or domain experts from OpenAI to Deepmind.


Nicolas Bustamante: spent 7 years building one of the largest AI-driven legal search engines (Bloomberg for lawyers). Nicolas hired nearly 200 people, secured millions of dollars in debt and equity funding, and the profitable business was successfully acquired by Summit Partners, a $43B billion growth equity fund, for $x00M+

Edouard Godrey: worked for nine years at Apple, leading teams of data scientists and engineers. He worked on Apple Search (Spotlight) and Apple Pay, maintaining big data pipelines and deploying cutting-edge AI models. He received the 2019 Apple Pay Innovation Award for outstanding contributions and fresh insights.

Our philosophy

Small team: small in-person teams outperform large and well-funded companies. When people visit our office, they should be surprised by how few people we are.

Ship code: we avoid meetings, PM jargon to release early, release often, and listen to customers.

In-person: we believe high-performing teams do their best work, build long-term relationships, and have the most fun in person.

Company Values

Clone and improve the best: we're not about reinventing the wheel but about enhancing proven success. We are shameless cloners who stand on the shoulders of giants. We draw inspiration and then create differentiation because distinctiveness drives dominance.

Release early, release often, and listen to your customers: speed matters in business, so we push better-than-perfect updates for customers asap. Mastery comes from repeated experiments and learning from mistakes rather than putting in a set number of hours. It’s 10,000 iterations, not 10,000 hours.

Warren Buffett: We model our personal and professional ethos on the principles he exemplifies. Upholding integrity, valuing honesty, practicing frugality, championing lifelong learning, embracing humility, extending generosity, applying rationality, and demonstrating patience. Every day, we strive to mirror these Buffett-inspired virtues.

Job Desc

We are building real-time data pipelines for millions of unstructured financial documents to feed our financial LLM. It’s cutting-edge data engineering at the AI frontier.

Tech stack: Spark/Databricks, Python, Elastic, Postgres and LLM. Knowing React, Next.js, and TypeScript is a plus.

Experience: 5+ years of deploying production code at a company with a large infrastructure.

Location: San Francisco

Contract: Full-time

Apply here

Interview Process

Please Apply here

30-minute Alignment Call A 30-minute call to ensure everyone's on the same page regarding project goals and expectations.

Tech Practical Interview in person in San Francisco A hands-on interview to evaluate technical skills and problem-solving abilities.

Reference Checks Contacting previous employers to verify work ethic and suitability for the position.

Job Offer A formal invitation to the selected candidate outlining the terms of employment.

The process is fast, it can last less than a week

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