Full-Time Market Data Engineer

Historical Data Capture and Storage: Design, develop, and maintain systems for the acquisition, storage, and retrieval of historical market data.

Data Integrity and Accuracy: Ensure the integrity and accuracy of historical market data, including data validation, cleansing, and normalization processes.

Data Architecture Development: Build and optimize data storage solutions, ensuring scalability and high performance for large volumes of time-series data.

Versioning and Reconciliation: Develop systems for data versioning and reconciliation to handle changes in exchange formats or corrections to past data.

Data Source Integration: Implement integrations with various market data providers, exchanges, and proprietary data sources to continuously collect and store historical data.

Data Access Tools: Build internal tools for easy access to historical data, ensuring performance, ease of use, and data integrity.

Collaborate with Trading and Research Teams: Work with quantitative researchers and traders to understand data requirements and optimize systems for data retrieval and analysis.

Performance and Scalability: Develop scalable solutions to handle growing volumes of historical data, ensuring efficient queries and data retrieval for research and backtesting.

Optimize Storage Costs: Optimize data storage solutions, balancing cost-efficiency with performance.

Compliance and Auditing: Ensure systems comply with regulatory requirements and assist in data retention, integrity, and reporting audits.

• Required Skills and Experience:
• Commercial experience with financial instruments.
• Familiarity with market data formats (e.g., MDP, ITCH, FIX, SWIFT, APIs).
• Strong programming skills in Python or Go (or Rust).
• ETL process and tools experience.
• Experience with distributed data systems (Hadoop, Kafka, Spark, etc.).
• Linux/Unix expertise.
• Commercial experience building large-scale time series data in financial services.
• Strong SQL proficiency.
• Bachelor's degree in Computer Science or related field.

• Preferred Qualifications:
• Experience in a proprietary trading firm or buy-side environment.
• Data governance and compliance experience.
• Containerization, orchestration (Docker, Airflow, SLURM).
• Cloud-based storage solutions (AWS S3, Google Cloud Storage, Azure).
• Familiarity with machine learning and data science.

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