Quant Data Lead

Job Summary

The Quantitative Equity group at Lazard Asset Management is seeking a skilled data engineer to lead the design and evolution of an end-to-end quantitative data ecosystem. This role involves developing high-quality pipelines and data products, defining and implementing data-modeling approaches, establishing core data-governance practices, and contributing to both the new and existing production data systems.

Responsibilities

• Lead the design and evolution of an end-to-end quantitative data ecosystem, including ingestion, storage, modeling, access, and governance.
• Develop high-quality pipelines and data products that support quantitative research, model development, production workflows, and analytics.
• Define and implement data-modeling approaches suited to quantitative equity workflows.
• Establish core data-governance practices across metadata, quality, lineage, and documentation.
• Evaluate, onboard, and integrate datasets and vendors; design scalable processes for ingesting market, fundamental, and alternative data.
• Contribute hands-on code, review designs, set engineering standards, and help recruit and mentor data engineers as the team grows.
• Support existing production data systems during the build-out and migration to the new ecosystem.

Requirements

• Bachelor’s or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field.
• 8–12+ years of experience in data engineering, data architecture, or quantitative data platforms.
• 5+ years of experience using technologies such as Snowflake, Databricks, Azure services or the like.
• Strong proficiency in data modeling.
• Hands-on experience building and operating data pipelines.
• Familiarity with market, fundamental, benchmark, and security-master datasets used in quantitative equity.
• Solid grounding in data governance and lineage.
• Ability to operate in a startup-style environment, balancing architecture, hands-on coding, and rapid iteration.

Qualifications

• Bachelor’s or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field.
• 8–12+ years of experience in data engineering, data architecture, or quantitative data platforms.
• 5+ years of experience using technologies such as Snowflake, Databricks, Azure services or the like.
• Strong proficiency in data modeling.
• Hands-on experience building and operating data pipelines.
• Familiarity with market, fundamental, benchmark, and security-master datasets used in quantitative equity.
• Solid grounding in data governance and lineage.
• Ability to operate in a startup-style environment, balancing architecture, hands-on coding, and rapid iteration.

Skills

• Data modeling.
• Data pipeline development.
• Data governance and lineage.
• Market, fundamental, benchmark, and security-master datasets.
• Startup-style environment operations.

Benefits

We offer a comprehensive benefits package that includes a competitive base salary range of approximately $200,000 - $240,000 USD, along with various factors contributing to the actual base compensation. The package also includes comprehensive benefits and may include incentive compensation.