Quantitative Developer

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MAIN DUTIES/RESPONSIBILITIES OF THE ROLE: Essential Responsibilities: Combine quantitative skills, strong data engineering literacy, and deep understanding of credit products to ensure that the firm's data architecture supports robust pricing, risk, and analytics. Work closely with portfolio managers, analysts, and traders to understand data and research requirements and build scalable solutions. Ingest, transform, and serve large-scale financial datasets across asset classes using Python, Snowflake, and NoSQL databases (e.g., MongoDB). Provide first-line production support, including triaging data issues, monitoring pipeline health, and quickly responding to front office needs. WORK EXPERIENCE/BACKGROUND: Essential 5+ years of professional experience as a FO engineer, ideally in a buy-side, sell-side, or trading environment. Deep expertise in Python, with strong software engineering practices (version control, testing, CI/CD). Proven track record of building robust data pipelines in cloud-native environments (preferably AWS). Experience with Docker and container-based deployments. Strong knowledge of Snowflake and NoSQL databases (especially MongoDB). Solid understanding of credit financial markets and instruments Excellent problem-solving skills, with a proactive and ownership-driven mindset. Ability to work independently, communicate effectively, and collaborate in a dynamic front office setting. Willingness to participate in on-call or front-line production support Desirable Experience with market data providers (Bloomberg, Refinitiv, etc.) Familiarity with tools like Airflow, prefect, or other orchestration frameworks. Experience building internal tools or dashboards using Dash, Streamlit, or similar web-based data analytics platforms.

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Company Intel

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