<p>About the job :<br/><br/>- Data Engineer for financial datasets in a quant research & trading environment.<br/><br/>Key Responsibilities :<br/><br/> - Build Python-driven data ingestion pipelines from market & internal sources.<br/><br/> - Ensure data quality with automated validation & anomaly detection.<br/><br/> - Manage data vendors, optimize costs, & expand data pipeline.<br/><br/> - Collaborate with quants & engineers for seamless data access.<br/><br/>Requirements :<br/><br/> - Bachelor's/Master's in CS/Engineering/Data Science (Tier 1 colleges).<br/><br/> - 1-2 years in data engineering/software/Python.<br/><br/> - Strong Python (numpy, pandas), Git, financial data position offers a unique opportunity to work at the intersection of data engineering, quantitative finance, and high-performance computing.
</p><p><br/></p><p>Key Responsibilities : </p><p><br/></p><p>- Data Pipeline Development: Design, build, and maintain robust, scalable, and fault-tolerant data ingestion pipelines written primarily in Python to process high-volume, real-time, and historical data from various market data providers (e.g., exchanges, vendors) and internal trading systems.
</p><p><br/></p><p>- Data Quality Assurance: Implement and manage automated data validation, cleansing, and anomaly detection frameworks to ensure the highest level of data quality and integrity across all datasets used for research and production trading.
</p> (ref:hirist.tech)