Senior Data Developer

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Key Responsibilities

• Develop and maintain scalable Python-based ETL pipelines for ingesting and transforming market data from multiple sources.
• Build and manage cloud data lake solutions (AWS/Databricks) for storing and retrieving large volumes of structured and unstructured data.
• Implement rigorous data quality, validation, and cleansing routines to ensure the accuracy of financial time-series data.
• Optimize data workflows for low latency and high throughput, critical for quantitative research, trading strategies, and risk management.
• Collaborate with portfolio managers, quantitative researchers, and traders to tailor data solutions that support modeling, strategy development, and trading insights.
• Contribute to the firm's security master database design and implementation.
• Analyze and extract insights from datasets to inform trading and risk management decisions.
• Document system architecture, data flow processes, and technical solutions to ensure transparency and reproducibility.

Requirements

• Bachelor's (or higher) degree in Computer Science, Engineering, Mathematics, Statistics, or a quantitative discipline.
• At least 5 years of relevant experience in developing python-based financial software.
• Demonstrated expertise in Python, including data manipulation experience with Pandas.
• Some exposure to financial datasets across various asset classes.
• Experience collaborating with quantitative analysts to support the quantitative research and modeling process.
• Proficiency in working within a Linux environment.
• Strong foundation in mathematics and statistics.
• Ability to thrive in a fast-paced, detail-oriented environment under pressure.
• Excellent problem-solving skills along with strong verbal and written communication abilities.
• NYC or London based with some in-office presence required.

Preferred

• Experience with Kafka or other streaming technologies.
• Understanding of financial market data, symbology, and reference data across equities, futures, credit, indices, and OTC asset classes.
• Prior work in a hedge‑fund, prop‑trading, or other quantitative‑finance environment.
• Experience with cloud platforms such as Azure / AWS.
• Exposure to LLM/AI solution architecture and integrating AI/ML models into data pipelines.