Python Data Engineer

Location- Gurgaon / Noida

Onsite - 5 days in a week

Must-Have:

Python

Oops Concept

Data Structures, Algorithms

Libraries- NumPy, Pandas, SciPy, Scikit-learn

Git

Docker, CI/CD

MySQL

Key Responsibilities:

Design, develop, and maintain scalable Python-based quantitative tools and libraries.

Collaborate with quants and researchers to implement and optimize pricing, risk, and trading models.

Process and analyze large datasets (market, fundamental, alternative data) to support research and live

trading.

Must possess experience in developing and deploying applications within an enterprise environment that follows a well-established software development lifecycle (SDLC).

MySQL experience is mandatory for this position

Build and enhance backtesting frameworks and data pipelines.

Integrate models with execution systems and trading platforms.

Optimize code for performance and reliability in low-latency environments.

Participate in code reviews, testing, and documentation efforts.

Required Qualifications:

5+ years of professional experience in quantitative development or similar roles.

Proficiency in Python, including libraries like NumPy, Pandas, SciPy, Scikit-learn, and experience in object-

oriented programming.

Strong understanding of data structures, algorithms, and software engineering best practices.

Experience working with large datasets, data ingestion, and real-time processing.

Exposure to financial instruments (equities, futures, options, FX, fixed income, etc.) and financial mathematics.

Familiarity with backtesting, simulation, and strategy evaluation tools.

Experience with Git, Docker, CI/CD, and modern development workflows.

Preferred Experience with C++ for performance-critical modules.

Knowledge of machine learning techniques and tools (e.g., TensorFlow, XGBoost).

Prior experience in hedge funds, proprietary trading firms, investment banks, or financial data providers.