Market Data Connectivity Engineer

Responsibilities

• Actively participate in the daily operations of a high-volume data scheduling system based on Dagster; handle routine task monitoring, troubleshooting, and recovery/re-runs; and—under mentor guidance—rapidly adapt to and implement changes in exchange-level underlying protocols.
• Data
• Quality Assurance
• Develop data quality validation rules and automation scripts; perform initial analysis and diagnosis (first-line diagnosis) for data quality anomalies detected during daily operations.

Requirements

• 0-3 years relevant work experience, or an outstanding recent graduate/junior engineer with exceptional technical potential.

Preferred

• Understanding of common market data structures (e.g., order book, tick, bar).
• Experience participating in finance-related projects, competitions, or coursework.

Data Engineering Implementation

Execute the end-to-end backfill process for high-frequency MBO (Market-By-Order) historical data, managing everything from raw PCAP packet processing to the cleaning, standardization, and final delivery of high-fidelity MBO data.

Quantitative Research Support

Serve as a frontline point of contact to efficiently support quantitative researchers' data needs, assisting in identifying, explaining, and resolving complex issues related to market data encountered during the research and investment process.

Core Skills

Solid coding proficiency in C++ and Python; familiarity with Linux development environments. Experience with high-frequency tick data, time-series data, or large-scale distributed data processing is a plus.

Familiarity with Python and common data processing libraries (e.g., pandas, numpy) is preferred.

Strong interest in financial trading systems and data systems; excellent learning agility and teamwork skills.

Practical engineering project experience (e.g., coursework, internships, open-source projects) is preferred.