Job Description

Senior Data Engineer – Global Alternative Investment Firm

Location: Midtown Manhattan preferred (Hybrid with CTO, flexibility for the right candidate)

Global Offices: Operating on four continents

About the Firm

A global alternative investment firm with ~$9B in assets is expanding its technology and data capabilities as it scales across multiple investment strategies. With operations on four continents and a majority of revenue driven by its Private Equity platform, the firm is entering a growth phase and investing heavily in modernizing its data infrastructure.

The CTO is leading a strategic buildout of a new enterprise data environment and is seeking a hands-on, highly technical Data Engineer to help architect and implement the firm’s next−generation data platform.

Role Overview

We are looking for a Senior Data Engineer who enjoys both building and architecting. This role requires someone who can operate “in the weeds” while also understanding high-level business use cases across Private Equity, hedge fund strategies, and general financial services.

You will work directly with the CTO to design, construct, and optimize a modern data warehouse and analytics ecosystem, with a strong preference toward Microsoft technologies such as Microsoft Fabric, Azure, and Medallion Architecture.

This is a high−impact role where your work will directly influence investment, operations, and risk decision-making across the firm.

Why This Role

• Greenfield enterprise data platform build (not maintenance)
• Direct influence on investment, risk, and operating decisions
• True architecture + execution ownership
• Partnering closely with a CTO who is deeply technical
• Opportunity to standardize data across multiple strategies globally

Key Responsibilities

• Architect and build a cloud-based enterprise data warehouse for multiple investment groups
• Design robust data models, ETL/ELT pipelines, and scalable ingestion frameworks
• Implement and manage Medallion Architecture (Bronze/Silver/Gold) and data−lakehouse best practices
• Translate investment, operations, and risk use cases into clear technical data requirements
• Establish standards for data quality, governance, lineage, validation, and documentation
• Integrate third−party and proprietary datasets used across Private Equity, hedge−fund strategies, and public markets
• Collaborate with global teams to support analytics, reporting, and future automation/ML initiatives
• Act as both a strategic technical advisor to the CTO and a hands−on builder of the core data environment

Required Experience

• 5–10+ years of Data Engineering experience in Financial Services (required)
• Experience within Private Equity, Hedge Funds, Asset Management, or multi−strategy environments (strong plus)
• Hands-on experience with Microsoft Azure, Microsoft Fabric, Synapse, Databricks, or similar modern stacks
• Deep understanding of Medallion Architecture, Delta Lake, and data-lakehouse concepts
• Strong SQL, Python, and ETL/ELT engineering skills
• Experience designing scalable data models (Kimball/star schema, dimensional modeling)
• Ability to gather requirements and translate business needs into technical solutions
• Demonstrated success building modern data platforms from the ground up