Data Engineer

Lazard • New York, NY

1d • $170,000 - $200,000 • Hybrid

About The Position

Lazard Asset Management (LAM) is seeking a Data Engineer to join its Enterprise Data team and help advance the firm’s data journey. This role is responsible for the firm’s external market data ETL and warehousing, contributing to data architecture and cloud engineering design and delivering new data pipelines. It is a highly hands-on backend engineering role within a lean engineering team, where the successful candidate is expected to take ownership of problems, design practical solutions, and implement them end to end. We are looking for a highly motivated, organized, and experienced engineer with a strong sense of ownership, disciplined software development practices, and a focus on clean design, high reliability, and operational stability.

Requirements

• 5-10+ years of hands-on database and data warehouse engineering experience with external market data within a financial institution.
• 5+ years of advanced SQL expertise as applied to data engineering workloads.
• 5+ years of Azure cloud experience with focus on Azure data engineering services.
• 5+ years of hands-on experience with ETL techniques and processes, including identifying and resolving gaps, overlaps, and inconsistencies in market data feeds.
• 5+ years of experience in a team responsible for acquiring, ingesting, and managing external market data.
• Broad understanding of the systems and business processes supporting Middle Office and Back Office functions at investment banks or asset managers.
• Strong understanding of relational database technologies within financial institutions.
• Strong backend database development experience.
• Ability to work effectively both independently and as part of a team.
• Strong verbal and written communication skills.
• Knowledge of best practices for code quality, testing, and performance optimization.

Nice To Haves

• Experience with Snowflake, Databricks, and Sybase, including building historical data archives and designing schemas for time-series financial market data.
• Experience with DevOps practices, including GitLab CI/CD pipelines (both YAML and UI-based configurations).
• Experience with dbt (data build tool).
• Strong understanding of AI/ML concepts and implementations, including exposure to AI coding tools such as Claude Code or GitHub Copilot.
• Experience with Linux and shell scripting.

Responsibilities

• Contribute to the operational excellence of existing ETL workloads running on Snowflake, Databricks, and Sybase.
• Respond to end-user requests and troubleshoot issues related to data access, latency, and performance.
• Work with business and technology teams to understand their data consumption patterns and optimize them for performance and cost.
• Work closely with stakeholders to design new data delivery channels in Azure.
• Coordinate design, configuration, and deployment activities with Infrastructure teams.
• Use dbt (data build tool) for transformations between raw ingestion layers and curated downstream datasets.
• Use Python for scripting and automation to support data management.

Benefits

• Comprehensive, competitive benefits.
• Highly individualized employee experience that enables you to balance your commitments to career, family, and community.
• Investment in the development of your career.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed