Data Engineer

Lazard

. Contribute to the operational excellence of existing ETL workloads running on Snowflake, Databricks, and Sybase .

Posted 10/6/2026full-timeNew York City • New York • United StatesMid-LevelSenior💰 $170,000 - $200,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in database and data warehouse engineering, particularly with external market data in financial institutions. Proficient in Azure data engineering services, ETL processes, and optimizing data performance and cost.

Highest-signal resume keywords

Azure Data Engineering ServicesAdvanced SQL ExpertiseETL Techniques and ProcessesSnowflakeDatabricks

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Database EngineeringData Warehouse EngineeringETLData ManagementData ArchitecturePython ScriptingSQLDbtPerformance OptimizationAI/ML Concepts

Soft Skills

Problem SolvingTeam CollaborationCommunication

Tools & Technologies

SnowflakeDatabricksSybaseAzureGitLab CI/CDLinuxShell Scripting

Industry Keywords

Financial InstitutionsMiddle OfficeBack OfficeMarket DataData Consumption Patterns

Tech Stack

Tools & technologies

AzureCloudETLLinuxPythonShell ScriptingSQL

About the role

Key responsibilities & impact

Contribute to the operational excellence of existing ETL workloads running on Snowflake, Databricks, and Sybase
Respond to end-user requests and troubleshoot data access, latency, and performance issues
Work with business and technology teams to understand data consumption patterns and optimize performance and cost
Design new data delivery channels in Azure with stakeholders
Coordinate design, configuration, and deployment activities with Infrastructure teams
Use dbt for transformations between raw ingestion layers and curated downstream datasets
Use Python for scripting and automation supporting data management
Own problems, design practical solutions, and implement them end to end within a lean engineering team
Contribute to external market data ETL and warehousing, data architecture, cloud engineering design, and new data pipelines

Requirements

What you’ll need

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 applied to data engineering workloads
5+ years of Azure cloud experience focused on Azure data engineering services
5+ years of hands-on ETL techniques and processes, including identifying and resolving gaps, overlaps, and inconsistencies in market data feeds
5+ years of experience acquiring, ingesting, and managing external market data
Broad understanding of 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 independently and as part of a team
Strong verbal and written communication skills
Knowledge of best practices for code quality, testing, and performance optimization
Experience with Snowflake, Databricks, and Sybase, including historical data archives and schemas for time-series financial market data is a bonus
Experience with DevOps practices, including GitLab CI/CD pipelines, is a bonus
Experience with dbt is a bonus
Strong understanding of AI/ML concepts and implementations, including AI coding tools such as Claude Code or GitHub Copilot, is a bonus
Experience with Linux and shell scripting is a bonus

Benefits

Comp & perks

Comprehensive, competitive benefits
Individualized employee experience supporting balance between career, family, and community
Career development and investment in professional growth
Incentive compensation may be included