Overview
Full Time
Skills
FOCUS
Risk Management
Fixed Income
FX
Data Flow
Data Engineering
Mentorship
Physical Layer
Data Link Layer
Network Layer
Bloomberg
Management
Microsoft Exchange
Data Quality
Python
Data Analysis
Extract
Transform
Load
Market Analysis
Equities
Analytical Skill
Problem Solving
Conflict Resolution
Communication
Cloud Computing
Real-time
Data Processing
Financial Services
Trading
Job Details
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
Requirements
Preferred Qualifications
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.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.