Data Engineer

Data Engineer

We’re partnering with a technology-first global investment firm (~$70bn AUM) headquartered in Manhattan that has built a reputation for backing some of the most transformative technology companies of the past decade. Founded by an ex-Tiger Global Management PM, the firm combines long/short public investing with venture capital, taking long-term, high-conviction positions in some of the world’s most innovative businesses. Their venture arm was an early investor in companies like OpenAI, reflecting the firm’s deep roots in the technology ecosystem. With roughly 200 employees globally, the culture is intentionally lean, analytical and technology-driven, staffed largely by highly technical investors and engineers from top academic backgrounds. The firm runs with a single-manager investment structure, meaning teams are small, collaborative, and decisions are made quickly. They are now hiring a Data Engineer to join a small, high-impact data team of three supporting the investment platform.

The Opportunity

This role sits directly at the intersection of data engineering and front-office investing. You’ll work closely with portfolio managers, analysts, data scientists and AI engineers, helping transform complex datasets into insights that shape real investment decisions. Rather than operating in a back-office function, you’ll often be sitting alongside investors, helping answer questions such as how to evaluate emerging technology companies or how new data sources can inform research. The platform is cloud-native, and the team owns the full lifecycle of the firm’s data infrastructure—from ingestion and ETL to analytics and data quality. You’ll have significant ownership over large-scale SQL data systems (PostgreSQL preferred) while helping improve architecture, reliability and data workflows across the investment platform.

What you’ll be working on

• Designing and maintaining scalable ETL and data pipelines
• Building and optimising large SQL data models and analytics datasets
• Partnering directly with investment teams and data scientists on research workflows
• Improving data quality, governance and architecture across the firm
• Supporting a modern cloud-based data platform

What they are looking for

• Strong SQL expertise (this is heavily tested in interviews)
• Solid Python engineering background
• Experience building production data pipelines and ETL systems
• Strong communication skills and ability to work with both engineers and investors
• 2–5 years experience in data engineering or similar roles

No prior asset class experience is required — the team values strong engineering fundamentals and curiosity about markets.

The Team

You’ll report into the Head of Data, who built and leads the firm’s data platform. The group is intentionally small, high-calibre, and highly collaborative. The team tends to attract engineers from top universities and technical backgrounds comparable to leading quantitative trading firms, creating a very strong learning environment. This is an exceptional opportunity for a Data Engineer who wants to stay hands-on technically while working close to the investment decision-making process, particularly if you're excited by technology, venture investing and AI-driven companies. If you’re interested, feel free to apply or reach out directly for a confidential conversation.

Key skills/competency

• Data Engineering
• SQL
• Python
• ETL
• Data Pipelines
• Data Modeling
• Cloud Platform
• Data Quality
• Investment Data
• Front-Office