Senior Python Engineer - Backend & Data - Brazil

We are looking for a Senior Python Engineer with deep data understanding to lead a critical data infrastructure project for our biggest client, a finance and trading platform. The project centers on using Python to consolidate stale, fragmented data from multiple sources into a reliable, well-structured database, enabling the client's trading team to make faster and more informed decisions.

This is a data-heavy role, focused on aggregation, modelling, processing, and reliability. You will work closely with our internal team and directly with the client to extract domain knowledge, define the data model, and build a robust pipeline from the ground up.

Our Mission, Vision, and Values

At Space Inch, we prioritize alignment with our clients and team, ensuring a deep understanding of their needs. We are committed to delivering exceptional work while supporting the personal and professional growth of our team members.

Our Stance on AI & Technology Transitions

We don't just "accept" AI; we encourage its usage to enhance productivity and code quality. If you’re a Senior Engineer, AI-proficient, with a proven track record of picking up new languages quickly, you might be a great fit to our team. We value senior-level architectural thinking and problem-solving over rigid adherence to a specific syntax.

About working at Space Inch

• Our team is around 80 people, primarily based in Croatia, but also with members in South America, Serbia, and the US; the product team mostly being in the US, and engineering in Croatia and Brazil
• We are remote-first, but occasional travel may be required, e.g. for our annual company retreats
• We work on end-to-end projects with a long-term vision
• We prioritize work-life balance, even with a globally distributed team

What You’ll Be Working On

• Consolidate critical trading data from multiple disparate sources into a centralized, queryable database.
• Design and implement data pipelines and orchestration workflows to automate data ingestion and processing.
• Enable the client’s team to track position changes across daily, weekly, and monthly intervals with accuracy and speed.
• Propose and implement a database strategy using a lower-level database as the primary aggregation layer, with reporting published to Snowflake.
• Ensure data auditability and observability, with clear traceability for how each data point is created.
• Identify and surface additional data opportunities as the project matures, helping the client understand the broader potential of their data.