Quant Data Engineer

1 day ago

Singapore J&D Technology Pte Ltd Full time

This role focuses on developing and maintaining scalable data infrastructure for high-frequency trading systems. You'll design and automate pipelines to ingest, clean, and synchronize market data (minute, tick, L2) across C++ and Python layers, while managing performance on Linux servers. Key skills include Linux systems engineering, Python (pandas, multiprocessing, FastAPI), C++ (I/O, threading), and database management (ClickHouse/PostgreSQL). Familiarity with AI/ML tools and multi-agent frameworks is a plus. You'll gain hands‐on experience with real quant infrastructure, performance optimization, and agentic AI systems, working closely with quant and AI engineers. Strong performers can transition into full‐time Data or Systems Engineer roles. Responsibilities Data Infrastructure Development: Build and maintain scalable data pipelines for ingesting, transforming, and storing high-frequency market data (minute, tick, and L2). Linux Systems Engineering: Manage and optimize processes across Linux servers (file systems, permissions, cron jobs, daemons, I/O optimization). C++ Integration: Collaborate with developers to integrate C++ backtesting and data-processing modules into the broader data infrastructure. Automation: Implement tools to automate data ingestion, cleaning, and synchronization across Python and C++ layers. Multi-Agent Integration: Work with AI engineers to connect data pipelines into multi-agent research frameworks (feature generation, validation, and model retraining). Performance Optimization: Benchmark system performance, identify bottlenecks, and improve throughput and reliability. Monitoring & Validation: Build health checks and diagnostic dashboards for data quality and latency tracking. Requirements Strong knowledge of Linux systems, including shell scripting, environment setup, and process management. Proficiency in C++ (data structures, file I/O, multithreading preferred). Experience with Python (pandas, multiprocessing, or FastAPI) for ETL and data orchestration. Understanding of databases (ClickHouse, PostgreSQL, or similar). Basic familiarity with AI/ML workflows (LangChain, LLM agents, or data preparation for model training). Strong understanding of data engineering principles: pipeline design, error handling, schema evolution, and versioning. Interest in financial data and quantitative systems. What You'll Gain Hands‐on exposure to real‐world AI‐driven quant infrastructure. Experience working on high‐frequency, multi‐language systems (C++/Python/Linux). Direct mentorship from quant researchers and AI engineers building next-generation agentic systems. Opportunity to contribute to live research and production‐grade infrastructure. Pathway to a full‐time Data or Systems Engineer position upon strong performance. #J-18808-Ljbffr

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