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Niche quantitative backend role and senior band reduce applicant density despite metro location.
Requires deep backend, time-series, and quantitative domain expertise limiting cross-industry portability.
Explicit 7-10 years plus mandatory Python, microservices, DB, cloud and Kubernetes experience increases filter strictness.
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Develop and maintain Python-based microservices and automated workflows for quantitative trading data applications.
Design and maintain RESTful APIs interfacing with multiple databases including MongoDB, SQL Server, and PostgreSQL, focusing on time-series and quantitative data.
Optimize backend systems for performance, ensure system reliability via monitoring and logging, and manage CI/CD pipelines for backend services.
Strong proficiency in Python (3.9+) with data libraries like Pandas and NumPy.
7 to 10 years of relevant backend development experience with microservices, RESTful APIs, and databases (SQL Server, PostgreSQL, MongoDB).
Experience with containerization (Docker), cloud platforms (GCP/Kubernetes), and understanding of software engineering fundamentals.
Location: Gurgaon, Haryana, India; Employment Type: Permanent.
Experienced in designing enterprise-level data architectures and distributed backend systems in data-intensive environments.
Capabilities to independently manage complex codebases and collaborate with front-end teams on API design.
Prior exposure to financial or quantitative trading domains and real-time or streaming data handling is advantageous.