Senior/Lead Python Software Engineer

Project description

We are looking for a Senior/Lead Full-Stack Python Developer to drive the development of complex, data-intensive systems. This is a "hands-on" leadership role requiring a combination of full-stack capabilities. You will be responsible for building scalable backend engines, sophisticated data visualizations, and ensuring the seamless integration of machine learning models into production environments.
The ideal candidate is a "force multiplier"—someone capable of solving deep technical bottlenecks independently but who excels at leading a team toward a collective architectural goal. You don't just write code; you build systems that solve business problems.

Responsibilities

• Strategic Thinking: As a subject matter expert, you are expected to foresee architectural bottlenecks and potential security or scalability problems well in advance.

Full-Stack Ownership: Ability to operate as an agile developer solo or within a small team across the entire stack, leading the team through complex sprints.
Rapid Development: Execute in an Agile environment with a focus on high-velocity delivery without sacrificing system stability or code integrity.
System Architecture: Design and implement resilient microservices that handle high-volume data ingestion and real-time processing.
ML Implementation: Bridge the gap between data science and production, deploying Python-based machine learning models into live, high-stakes environments.
Technical Leadership: Conduct rigorous code reviews, mentor senior engineering staff, and define the long-term technical roadmap

SKILLS

Must have

• Expertise in FinTech: A proven track record of building secure, high-performance financial or trading platforms.

Lead Capacity: 5+ years of total experience (Python)
Complex Systems: Experience managing systems with intricate dependencies, real-time data needs, and cross-platform (Linux/Windows) requirements.
Agile Mastery: Deep understanding of Agile methodologies and the ability to pivot quickly in a fast-paced development cycle.
ML Productionization: Lead the effort to deploy and monitor Python-based machine learning models in live, high-stakes FinTech environments.
Data Fluency: Deep experience using Pandas for complex data transformations and Plotly for stakeholder-facing visualizations.
Backend: Python (FastAPI/Flask/Django), AsyncIO, and Machine Learning integration.

Nice to have

Domain Knowledge: Experience or strong interest in Power Markets and global energy data.
Infrastructure: Advanced knowledge of containerization and orchestration (Podman/Docker).