Market Data Connectivity Engineer

Metabit Technology LLC; Singapore; On-site; SGD 70,000 - 110,000; Full time

Job summary

Metabit Technology LLC is seeking a junior engineer to contribute to data engineering for high-frequency market data. The role involves implementing backfill processes, maintaining data pipelines, and supporting researchers with data needs across time-series datasets.

The ideal candidate has strong C++ and Python skills, experience with Linux, and a passion for financial trading systems. Prior exposure to Pandas/NumPy and distributed data processing is advantageous as you grow in a fast-paced,

Qualifications

• 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 data processing libraries (Pandas, NumPy) preferred.

Responsibilities

• Data Engineering Implementation: Execute end-to-end backfill for high-frequency MBO historical data, handling raw PCAP processing to cleaning, standardization, and delivery.
• Data Pipeline Operations & Adaptation: Participate in daily operations of a high-volume data scheduling system (Dagster); monitor, troubleshoot, and recover/re-run as needed; adapt to protocol changes.

Skills

C++

Python

Linux

Time-series data

High-frequency data

Pandas/Numpy

Job description

Job Responsibilities

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.

Data Pipeline Operations & Adaptation: 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.

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.

Job Requirements

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

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.

Bonus Points

Understanding of common market data structures (e.g., order book, tick, bar).

Experience participating in finance-related projects, competitions, or coursework.