Data Quality Engineer, Market Data

Overview

As a Data Quality Engineer, you will support the team in ensuring the highest quality of market data from both historical and real-time feeds. You will help build and maintain robust, asset-specific data quality processes that are critical to the firm’s trading and risk management operations. This is a hands-on role where you will learn from experienced engineers and contribute to the reliability of business-critical data.

Key Responsibilities

• Assist in monitoring, validating, and improving the quality of L1, L2, and L3 market data feeds for equities and futures from vendors and exchanges.
• Help develop and maintain automated data quality checks for various asset classes.
• Support efforts to ensure both historical and real-time data are accurate and aligned.
• Participate in proactive monitoring of data pipelines and alerting for anomalies or data issues.
• Assist in investigating and resolving data quality issues, working with engineering, vendor, and business teams.
• Contribute to documentation of data quality metrics, issues, and resolutions.
• Learn and apply best practices in data quality engineering and automation.

Requirements

• 3-5 years of experience in data engineering, data quality, or a related field.
• Exposure to L1/L2/L3 market data feeds for equities and/or futures from vendors such as Refinitiv or Bloomberg is a plus.
• Proficiency in Python for data analysis and automation.
• Understanding of data pipelines, ETL, or related systems.
• Strong analytical and problem-solving skills.
• Good communication skills and willingness to learn.

Preferred Qualifications

• Experience with cloud-based data platforms or distributed systems.
• Familiarity with real-time data processing frameworks.
• Interest in financial markets or prior experience in a financial services environment.