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Mid-level generalist backend role, metro location, and broad required skillset increase applicant competition.
Core backend and data engineering skills are transferable, though finance/time-series experience is preferred.
Explicit 3–6 years plus many mandatory backend, database, cloud, and CI/CD skills.
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Develop and maintain microservices and workflows primarily in Python for analytical, data-driven web applications in a quantitative trading environment.
Design and manage RESTful APIs serving time-series and quantitative data, ensuring collaboration with front-end developers to meet UI data needs.
Optimize backend performance including query tuning, job dependency management, and ensure system reliability through monitoring, logging, and CI/CD pipeline maintenance.
3 to 6 years of experience with backend development, specifically Python (3.9+) and data manipulation libraries like Pandas and NumPy.
Proficiency with microservices frameworks such as FastAPI and experience with both relational (SQL Server, PostgreSQL) and NoSQL (MongoDB) databases.
Working knowledge of containerization (Docker) and cloud platforms (GCP/Kubernetes).
Experience designing and implementing RESTful APIs and strong skills in software engineering fundamentals including debugging distributed systems.
Experienced in enterprise-level data architecture, capable of independently working within complex existing codebases.
Comfortable integrating backend services with front-end applications, focusing on clear API design and business logic placement.
Familiar with event-driven architectures and optimizing system performance in high-volume, financial or analytical domains.