Python Developer / Lead (Data Projects)
Summary
Build and maintain Python-based asset-management tools, integrate data pipelines, and support legacy systems while ensuring financial compliance and scalability.
We are looking for a talented Python Developer to join our technology team. This is an initial 12-month contract with the possibility of extension, as it is part of a long-term project.
The ideal candidate will have strong expertise in Python development for financial applications, experience working with data-driven solutions , and a good understanding of asset management principles. You will support legacy systems and facilitate integration between platforms.
Key Responsibilities:
- Design, develop, and maintain Python-based applications for asset management.
- Work on data processing, automation, and analytics for investment and trading teams.
- Develop and maintain APIs for data integration and system interoperability.
- Collaborate with quants, portfolio managers, and analysts to develop technology-driven solutions.
- Support and enhance existing applications built with .NET (C# or VB.NET) as needed.
- Optimize code performance and ensure scalability for large datasets.
- Implement cloud-based solutions (AWS, Azure, or GCP) for enhanced performance.
- Ensure compliance with financial industry security and regulatory standards .
Key Requirements:
- 5+ years of experience as a Python Developer, preferably in the financial or asset management industry.
- Strong knowledge of Python frameworks such as Django, Flask, or FastAPI.
- Good understanding of data structures, algorithms, and object-oriented programming (OOP) .
- Experience with SQL and NoSQL databases (PostgreSQL, MySQL, MongoDB).
- Background in other technologies is a plus.
- Familiarity with financial instruments, risk modeling, and asset management concepts.
- Knowledge of DevOps, CI/CD pipelines, and containerization (Docker, Kubernetes) is a plus.
- Strong problem-solving skills and ability to work in a fast-paced environment.
Preferred Qualifications:
- Experience with cloud platforms (AWS, Azure, or GCP).
- Understanding of financial data providers (Bloomberg, Reuters, FactSet).
- Knowledge of big data technologies (Spark, Hadoop) is an advantage.
Argyll Scott Consulting Pte Ltd