Hygge Software

Location: Warsaw

The Project
You'll be joining a platform that's redefining how private capital markets operate — think PE firms, venture funds, and hedge funds using AI to make faster, smarter decisions on complex financial data.
This isn't a maintenance role. You'll be one of the key engineers shaping the data foundation of an AI-native PaaS/SaaS product from the ground up: designing schemas that LLMs can actually reason over, building pipelines that don't fall apart under real enterprise load, and untangling the legacy architecture that got the product to where it is today.
The problems are genuinely hard. The data is messy, the domain is complex, and the stakes are high — which is exactly what makes it interesting.

What You'll Be Working On
 

• Architect cloud-native data topologies and AI-friendly ontologies for structured and unstructured financial data
• Design and own scalable ETL/ELT pipelines using Prefect or Airflow
• Reverse-engineer and optimize existing data infrastructure

• Implement data governance, security standards, and CI/CD practices across the data layer

   

What We're Looking For

Must-have:

• 3+ years with Python (Pandas, ETL frameworks)
• 5+ years with complex SQL and RDBMS
• 5+ years of ETL orchestration (Airflow, Prefect)
• Hands-on experience with cloud DW: Redshift, Snowflake, or RDS
• Strong grasp of data modeling — OLAP, OLTP, Star/Snowflake schemas
• English B2+ — you'll communicate directly with the founding team

Nice to have: Docker, Kubernetes, PySpark, AWS Lambda, cloud certifications

Why This Role
 

• You'll have real architectural ownership, not just ticket execution
• The domain (private capital + AI) is genuinely niche and growing fast
• Direct access to founders — short feedback loops, no bureaucracy
• A team that takes engineering quality seriously and actually means it
   

Hiring Process Intro call → Technical Interview → Final with Founding Team