What are the responsibilities and job description for the Financial Data Engineer - Top NYC Hedge Fund position at Mondrian Alpha?
A leading multi-strategy investment firm is seeking a Data Engineer to join its data platform team. This role sits at the core of the investment process, responsible for designing, building, and maintaining high-performance data systems that power trading, research, and risk across the firm.
The ideal candidate has experience working with financial datasets (market, reference, or trading data) and is comfortable operating in a fast-paced, front-office environment where data quality, speed, and reliability are critical.
Role Responsibilities
- Design, build, and maintain scalable data pipelines for ingesting and processing large volumes of financial data
- Develop and support infrastructure for market data (real-time and historical), reference data, and trading data
- Integrate external data sources such as Bloomberg (BPIPE), exchanges, and third-party vendors
- Ensure data accuracy, completeness, and timeliness across critical datasets used by trading and research teams
- Partner closely with portfolio managers, quants, and developers to deliver data solutions that support investment strategies
- Optimize data storage and retrieval for performance-sensitive use cases
- Contribute to the architecture and evolution of the firm’s data platform, including streaming and batch frameworks
- Troubleshoot data issues and implement monitoring/alerting to maintain high system reliability
Required Qualifications
- 2–5 years of experience in data engineering, preferably in a financial services or trading environment
- Strong experience working with financial datasets (market data, reference data, trading/transaction data, etc.)
- Hands-on experience with time-series databases, ideally KDB /q
- Proficiency in Python (or similar) for data processing and pipeline development
- Experience working with real-time data feeds (e.g., Bloomberg BPIPE, exchange feeds, or similar)
- Solid understanding of data modeling, ETL/ELT pipelines, and distributed systems
- Experience with SQL and large-scale data storage solutions
Preferred Qualifications
- Familiarity with streaming technologies (Kafka, Flink, etc.)
- Experience with cloud-based data infrastructure (AWS, GCP, or Azure)
- Exposure to tick data, order book data, or high-frequency datasets
- Understanding of asset classes (equities, futures, FX, options, etc.)
- Experience supporting front-office or trading systems