Data Engineer

My client is a leading Asset Management Firm in New York. They are looking for a data/software engineer to join their team. You MUST be local to NYC, you MUST be authorized to work in the US without sponsorship and you MUST be okay going to the office.

You MUST have experience with Python and either SQL or Snowflake.

You ideally have a degree in engineering. You also need to come from financial services!

********** THEY WILL NOT HIRE YOU IF YOU HAVE MORE THEN 6 YEARS OF EXPERIENCE, PLEASE DO NOT APPLY IF YOU HAVE MORE*****************

Company Overview

A leading investment management platform focused on providing flexible capital solutions to middle-market firms is seeking to expand its technology team. The firm partners closely with private equity sponsors and portfolio companies, delivering financing solutions across multiple asset classes. With a strong track record and significant capital under management, the organization operates across several major U.S. markets and emphasizes innovation, collaboration, and disciplined execution.

Role Overview

This role sits within the Investment Technology team and focuses on building and enhancing core data and application infrastructure that supports front-office and business operations. You'll work across data engineering, reporting, and internal tool development-helping modernize systems and improve how investment and operational teams access and leverage data.

The position offers strong exposure to business stakeholders and the opportunity to work on high-impact initiatives across data pipelines, analytics, and workflow automation.

Key Responsibilities

• Support and optimize cloud-based data warehouse environments to ensure scalable and efficient data access
• Build and maintain data pipelines that integrate multiple internal and external systems
• Develop internal tools, automation workflows, and lightweight applications to improve operational efficiency
• Create and maintain dashboards and reporting solutions used by senior stakeholders for decision-making
• Partner cross-functionally with investment, operations, finance, and analytics teams on data-driven initiatives
• Help define and implement best practices across data management, reporting, and system architecture
• Contribute to ongoing system integrations and enhancements across the broader technology stack