Lead Data Quality Engineer, Market Data

Overview

As Lead Data Quality Engineer, you will be responsible for both hands-on data quality engineering and leading a small team of data quality engineers. Your primary focus will be to ensure the highest quality of market data from both historical and real-time feeds. You will drive the development and maintenance of robust, asset-specific data quality processes that are critical to the firm’s trading and risk management operations. This is a business-critical role where clean, reliable data is a top priority and directly impacts the firm’s performance.

Key Responsibilities

• Lead and mentor a team of data quality engineers, providing technical guidance and prioritizing team deliverables.
• Monitor, validate, and improve the quality of L1, L2, and L3 market data feeds for equities and futures from vendors and exchanges.
• Develop and maintain automated, asset-class-specific data quality checks, including equities, futures, fixed income, FX, and more.
• Ensure both historical and real-time data are aligned, accurate, and fit for business-critical use.
• Proactively monitor data pipelines and set up ongoing alerting for anomalies or data issues.
• Investigate and resolve data quality issues, collaborating with engineering, vendor, and business teams.
• Analyze data flow and transformation logic to identify and address potential quality gaps.
• Document data quality metrics, issues, and resolutions.
• Contribute to the design and implementation of robust data quality frameworks and tools.

Requirements

• 5+ years of experience in data engineering, data quality, or a related field.
• Prior experience leading or mentoring technical teams.
• Proven experience working with L1/L2/L3 market data feeds for equities and futures from Refinitiv, Bloomberg, and direct exchange.
• Demonstrated expertise in running data quality checks and anomaly detection for both equities and futures, including real-time and historical data.
• Strong proficiency in Python for data analysis, validation, and automation.
• Solid engineering background with experience in data pipelines, ETL, or related systems.
• Deep understanding of market data structure, symbology, and common quality issues for both equities and futures.
• Excellent analytical and problem-solving skills.
• Strong communication skills and ability to work cross-functionally.

Preferred Qualifications

• Experience with cloud-based data platforms and distributed systems.
• Familiarity with real-time data processing frameworks.
• Prior experience in a financial services or trading environment.