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Intelliswift

Senior Python Developer

Intelliswift, Mc Lean, Virginia, us, 22107

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Pay rate range: $75/hour. to $80/hr. on W2 Location: Full-time on-site

Must Have Qualifications: 5+ years of relatable hands-on experience as a Python Developer, Django/Flask/FastAPI, NumPy, pandas, and Relational Database, Unit Testing

Position Overview: The Financial Engineering team is seeking a Senior Python Developer for a large strategic financial project. The position is focused on Python development of components for a software application platform that produces enterprise-level reporting based on financial statements and models. The candidate will develop and support the middle layer of the application to build, test, and deploy RESTful APIs-based services, create shared services components, and collaborate with other IT groups, DevOps, and User Interface teams.

Responsibilities include: • Senior engineer capable of designing solutions, writing code, testing code, automating tests, and deploying • Develop and maintain high-quality software code and automated tests (including Unit, Functional, Performance, Acceptance) for a web interface application that integrates data, analytics, and reporting components • Predictable results: changes in code can be proven to be correct and bug-free • Production resilience: the system must be highly available with minimal downtime • High performance: develop scalable calculations to maintain performance over large data sets • Ready, willing, and able to pick up new technologies and pitch in on story tasks (design, code, test, CI/CD, deploy, etc.)

Technical Skills: • Experience writing Python code and RESTful web services using frameworks such as Flask, FastAPI, etc. in a professional environment • Back End Skills: Python, Django/Flask/FastAPI, NumPy, pandas, and Relational Database • Automation Testing: Pytest, Unitest, Monkey patch, pytest-mockito, etc. • Build CI/CD Tools: gradle, Jenkins, git, Conda, pip, Jira, Gitlab, Confluence • DevOps: Linux & Docker

Preferred Qualifications: • Bachelor's degree, ideally in Computer Science, Financial Engineering or a related quantitative discipline • Prior experience with financial services companies is desired but not necessary