We are seeking a Senior Quantitative Data Engineer to support and enhance our automated trading infrastructure. You will work closely with researchers, traders, and execution teams to build reliable data pipelines, automate workflows, investigate production issues, and ensure the availability and quality of data powering our live trading systems.
This role provides exposure to quantitative research, trading operations, and large-scale financial datasets. You will own critical systems end-to-end and drive improvements in reliability, scalability, and operational efficiency.
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Design, develop, and maintain robust data pipelines and ETL workflows.
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Build tools for data onboarding, validation, reconciliation, and monitoring.
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Drive automation to eliminate manual operational processes.
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Work with large structured and time-series datasets using Python and modern data libraries.
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Optimize database schemas, storage, and data access patterns.
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Ensure the accuracy, completeness, and consistency of datasets used in research and live trading.
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Develop automated data quality checks and anomaly detection frameworks.
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Support researchers in cleaning, enriching, and featurizing datasets.
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Investigate and resolve discrepancies across multiple data sources.
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Own and proactively monitor production data pipelines and critical trading processes.
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Perform root-cause analysis and implement long-term preventive solutions.
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Troubleshoot issues involving APIs, brokers, exchanges, and third-party data vendors.
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Ensure high availability and reliability of mission-critical systems.
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Participate in production support during market hours and respond to time-sensitive issues.
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Drive improvements in data infrastructure, scalability, and operational efficiency.
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Establish best practices for monitoring, alerting, logging, and observability.
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Design fault-tolerant and maintainable systems.
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Improve deployment and release processes.
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Partner with quantitative researchers, traders, and software engineers to deliver reliable solutions.
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Coordinate with external vendors, brokers, exchanges, and data providers.
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Document systems, workflows, and operational procedures.
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Mentor junior engineers and contribute to technical excellence across the team.
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5+ years of experience in Data Engineering, Quantitative Engineering, or Data Operations.
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Strong Python programming skills and experience with Pandas, Polars, NumPy, and PyArrow.
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Expertise in SQL (PostgreSQL, MySQL, MSSQL) and database design.
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Strong Linux and shell scripting skills.
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Experience designing and maintaining ETL and data processing pipelines.
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Excellent debugging and root-cause analysis skills.
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Experience working in production environments with high reliability requirements.
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Strong communication and collaboration skills.
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Ability to work effectively in a fast-paced, live trading environment.
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Experience with financial datasets, market data, and corporate actions.
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Knowledge of equity, futures, and options markets.
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Experience with Bloomberg, Refinitiv, NSE/BSE, or exchange data.
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Familiarity with Redis/KeyDB, Kafka, RabbitMQ, Celery, or other messaging systems.
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Experience with Parquet and columnar data formats.
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Exposure to cloud platforms (AWS/GCP).
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Experience with monitoring and observability tools.
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Experience with FastAPI and REST APIs.
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Familiarity with ClickHouse or time-series databases.
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Experience with Docker and CI/CD pipelines.
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Knowledge of distributed systems and multiprocessing.
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Exposure to quantitative trading systems and research workflows.
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Opportunity to work on mission-critical automated trading systems.
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High ownership and autonomy.
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Exposure to quantitative research and live trading operations.
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Fast-paced environment with direct impact on business outcomes.
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Opportunity to mentor others and shape the evolution of the firm's data infrastructure.
