Market Data Connectivity Engineer

Metabit; Singapore; On-site; SGD 70,000 - 120,000; Full time

Job summary

Metabit in Singapore is seeking a data engineer to implement end-to-end backfill for high-frequency Market-By-Order data, from raw PCAP processing to cleaning, standardization, and delivery of high-fidelity datasets.

You will work with Dagster for data scheduling, monitor tasks, recover runs, and adapt protocols under mentorship; emphasis on learning agility, teamwork, and supporting researchers with market data questions.

Qualifications

• Background in data engineering or related field with 0–3 years of experience or a strong recent graduate.
• Solid coding in C++ and Python; Linux development environment familiarity.
• Experience with high-frequency tick or time-series data is a plus.
• Familiarity with Python data processing libraries such as pandas and numpy is preferred.
• Interest in financial trading systems and data systems; good teamwork and learning agility.
• Practical project experience (courses, internships, open-source) is a plus.

Responsibilities

• Data Engineering Implementation: execute end-to-end backfill for high-frequency MBO data from raw PCAP processing to cleaning, standardization, and delivery.
• Data Pipeline Operations: participate in Dagster-based scheduling, monitor tasks, troubleshoot, and recover/re-run processes; adapt to protocol changes.
• Data Quality Assurance: create data quality rules and automation scripts; perform initial diagnosis for data quality issues.
• Quantitative Research Support: assist researchers with data needs, identifying and resolving complex market data issues.

Skills

C++ proficiency

Python proficiency

Linux development

Education

Bachelor's degree or equivalent

Tools

Pandas

NumPy

Dagster

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.