Python Backend Developer - Startup Environment | daixta intelligence

**Overview**

daixta intelligence is developing cutting-edge financial intelligence infrastructure that enables institutions and individuals to engage with financial data more transparently and effectively. We're seeking a Backend Infrastructure Engineer passionate about tackling genuine system and data challenges in our dynamic early-stage environment. This position requires engineers who thrive on rapidly developing and deploying foundational systems.

If you flourish in highly organized enterprise settings with numerous specialized departments, this opportunity might not align with your preferences.

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Responsibilities **

• Architect and develop backend APIs and services utilizing Python • Create systems for processing and organizing financial datasets • Construct clean, modular backend solutions that seamlessly integrate with analytical processes • Collaborate extensively with machine learning and product teams on data processing workflows • Execute backend functionality for data analysis and reporting features • Maintain service reliability, scalability, and maintainability standards • Engage actively in system architecture planning and engineering strategy discussions

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Requirements **

**Essential

Qualifications :** • Proven expertise in Python backend development • Hands-on experience creating REST APIs with FastAPI or Flask • Proficiency in data processing and working with structured datasets • Competency managing JSON, CSV files, and data pipeline operations • Solid grasp of API architecture and backend system design principles • Capability to produce clean, modular, and sustainable backend code • Self-motivated approach suitable for startup dynamics • Willingness to complete technical assessment during recruitment

**Preferred

Qualifications :** • Background with financial or transactional data systems • Document or PDF processing experience • PostgreSQL database knowledge • AWS application deployment experience • Docker containerization familiarity • Collaboration experience with ML engineers or data pipeline teams

**Hiring Process:** Technical challenge, engineering discussion, team integration.

Monday to Friday, 9 AM – 5 PM (full-time)