Data Engineer

Overview

• Collaborate with cross-functional teams to deliver scalable data solutions for research and trading workflows.
• Lead the execution of market data strategies, ensuring high-quality datasets for operational and investment use.
• Analyze and remediate data quality issues, implementing scalable solutions to enhance data integrity.
• Manage vendor relationships, optimize contracts, and oversee licensing compliance for market data providers.
• Drive cross-functional data initiatives, coordinating project scope, timelines, and success metrics.
• Act as a bridge between business stakeholders and engineering teams to translate requirements into actionable solutions.
• Contribute to the development of monitoring frameworks and reporting mechanisms for data quality management.
• Work in a hybrid environment, combining on-site collaboration with remote flexibility.

Key Responsibilities & Duties

• Perform hands-on data analysis using Python and SQL to support investment workflows.
• Identify and address data quality issues, partnering with engineering teams for scalable solutions.
• Gather complex business requirements and translate them into functional specifications for data solutions.
• Lead cross-functional data projects, managing timelines, dependencies, and success metrics.
• Manage relationships with market data vendors, ensuring compliance and optimizing contracts.
• Monitor data usage, licensing, and entitlements, contributing to vendor strategy and cost optimization.
• Collaborate with investment and technology teams to enhance data acquisition and consumption processes.
• Develop frameworks for data quality monitoring and reporting in partnership with investment teams.

Job Requirements

• Bachelor of Science (BS) degree in a relevant field.
• 5-7 years of experience in data engineering or market data roles within financial services.
• Proficiency in Python and SQL for data analysis and problem-solving.
• Experience with market data vendors like Bloomberg, LSEG, and ICE Data Services.
• Understanding of financial markets and asset classes, including commodities and equities.
• Strong analytical skills and ability to balance technical and business priorities.
• Experience with AWS cloud environments and modern data architecture.
• Excellent communication and stakeholder management skills.