Python Engineer – Data Extraction

Quartr is a software company serving the world of finance. Every day, leading companies and financial institutions worldwide use our products to research faster and understand deeper.

For too long, markets have been obsessed with numbers. Everyone has access to the same quantitative data, while qualitative insights – the words, the signals, the nuance – have remained mostly in the shadows. We make those insights accessible, searchable, and actionable.

Our products are used daily by some of the most sophisticated teams in finance and tech, including major hedge funds and Magnificent 7 companies, and over a million finance professionals have downloaded our mobile app.

We're backed by some of the smartest minds in our industry and growing fast at a global scale, and we're still at the very beginning of what we expect to be a multi-decade journey.

Our Document Extraction team turns unstructured financial content into reliable, structured knowledge. We work with financial filings, earnings call slide decks and earnings call transcripts.

The goal is not just to pull text off a page, but to understand what a document means, structure it cleanly, and produce knowledge that downstream teams and products can trust.

We are looking for a Senior Engineer to own the extraction and structuring pipelines end to end. You will design the systems that ingest messy, real-world documents and output accurate, well-modeled data at scale. This is a hands-on engineering role with deep ownership, suited to someone who is equally comfortable building robust pipelines and reasoning about data quality.

• Professional experience as a backend engineer with a focus on Python
• A keen interest in NLP and large language models.
• Experience designing data schemas and building pipelines that produce structured, validated output.
• Solid backend architecture skills for creating scalable and maintainable systems
• Experience working with AWS
• Proficiency with Docker for managing and deploying backend services
• Practical experience with document AI, OCR, or information extraction from PDFs and other unstructured formats.
• Hands-on experience with NLP and large language models, including prompting, fine-tuning, or retrieval-based approaches.

We include occupational pension for all employees in Sweden.

Note: We are not seeking assistance from consultants or recruitment agencies.