Data Engineer - Greenfield Build - Boutique Global Hedge Fund

Mondrian Alpha; New York (NY); On-site; USD 180,000 - 240,000; Full time

Job summary

Mondrian Alpha is building a new data engineering function at a boutique global hedge fund in New York. You will design and implement foundational data pipelines, establish the data warehouse, and set standards that influence portfolio management, research, and risk teams from day one.

You will partner with PMs and researchers to align on data needs, implement monitoring and quality checks, and help define the stack of market data, cloud infrastructure, and orchestration tools as the team scales.

Qualifications

• 4+ years building production data pipelines; exposure to financial markets data preferred but not required.
• Strong SQL and Python fundamentals; production-grade code, not scripts.
• Experience with cloud data infrastructure (AWS, GCP, or Azure) and a modern orchestration tool (Airflow, Dagster, or similar).
• Track record of building something from scratch, not only maintaining an existing system.

Responsibilities

• Design and build the firm's core data pipelines from the ground up, covering market data, reference data, and internal trading data.
• Architect the data warehouse and set the standards, naming conventions, and documentation practices the team will run on.
• Partner directly with portfolio managers and researchers to understand what data they need and how fast.
• Build monitoring and data quality checks that catch problems before they reach a PM's dashboard.
• Evaluate and select the core tooling and vendors that define the stack.
• Mentor future hires as the team scales beyond its initial headcount.

Skills

SQL

Python

Production data pipelines

Cloud data infra

Airflow

Dagster

Data warehousing

Tools

Airflow

Dagster

Spark

Databricks

Job description

This role sits at the foundation of a brand-new data engineering function at a boutique global hedge fund entering its next phase of growth. The data engineer hired here designs the pipelines, schemas, and infrastructure that every downstream team, portfolio management, research, and risk, will depend on from day one. Get the foundation wrong and every analysis built on top of it inherits the problem; get it right and it becomes the backbone of how the fund makes decisions for years.

What You'll Do

• Design and build the firm's core data pipelines from the ground up, covering market data, reference data, and internal trading data
• Architect the data warehouse and set the standards, naming conventions, and documentation practices the team will run on
• Partner directly with portfolio managers and researchers to understand what data they need and how fast
• Build monitoring and data quality checks that catch problems before they reach a PM's dashboard
• Evaluate and select the core tooling and vendors (market data providers, cloud infrastructure, orchestration) that define the stack
• Mentor future hires as the team scales beyond its initial headcount

Must-haves

• 4+ years building production data pipelines; exposure to financial markets data (hedge fund, bank, or prop trading background) preferred but not required
• Strong SQL and Python fundamentals, comfortable writing clean, maintainable, production-grade code, not scripts. This is non-negotiable for the role
• Experience with cloud data infrastructure (AWS, GCP, or Azure) and a modern orchestration tool (Airflow, Dagster, or similar)
• A track record of building something from scratch, not only maintaining an existing system
• Comfortable operating with minimal process on a small team, and comfortable being the one who sets it

Nice-to-haves

• Exposure to machine learning pipelines or feature engineering, even at a hobbyist level
• Experience with time-series or tick data specifically
• Familiarity with Spark, Databricks, or other large-scale processing frameworks
• Prior experience at a quant fund, systematic strategy desk, or trading technology team

Who should apply

Strong data engineers from banks, prop shops, or top-tier tech are encouraged to apply even without hedge fund experience. Fundamentals matter more than pedigree here.

Why This Role

This is a ground-floor seat: the team doesn't exist yet in its final form, and the first data engineer hired shapes its architecture, its standards, and its early hires. Comp is top of market for a role with this level of ownership. The fund is small enough that one person's work is visible across the whole business, and senior enough that the work matters immediately, not in a year. For a data engineer who wants to build something rather than maintain it, this is that.