Data Engineer

Overview

On Site
Depends on Experience
Full Time

Skills

Continuous Delivery
Incident Management
Trading
Python
Data Engineering
Automated Testing
Bloomberg
Quantitative Analysis
Capital Market
Equities
IEX
Snow Flake Schema
Amazon Web Services
Continuous Integration
Data Quality

Job Details

No sponsorship available—our client requires candidates to be holders.

 

 

Job Title: Data Engineer Capital Markets 

Location: 100%-Onsite Manhattan, NY (5 days/week) Type: Full-Time W-2 Employee Compensation: $140-150K Base + Benefits, PTO, 401(k) Match Industry: Hedge Fund / Quantitative Trading

 

Role Overview

Join my client's team as a Data Engineer supporting a top-tier hedge fund in NYC. You ll build and maintain high-performance data pipelines for equities trading, working with cutting-edge tools like DBT, Dagster, Snowflake, and Python. This role demands deep capital markets expertise and a passion for production-grade engineering.

 

Responsibilities

  • Build modular, testable data pipelines for equities analytics

  • Develop Dagster jobs, ops, and assets for reliable orchestration

  • Integrate Snowflake (AWS) with upstream sources and internal models

  • Write clean Python code for pipeline logic and reusable components

  • Collaborate with quants and analysts to deliver trusted datasets

  • Monitor data quality, lineage, and execution using Dagster observability

  • Follow best practices in CI/CD, versioning, and recovery

 

Qualifications

  • 3 6 years in data engineering; 2+ in capital markets (hedge fund/trading firm preferred)

  • Strong SQL and Python skills

  • Hands-on with DBT and Dagster

  • Experience with Snowflake on AWS

  • Deep understanding of equities data (pricing, reference, corporate actions)

  • Comfortable with production systems and incident response

 

Preferred

  • Familiarity with Dagster asset-based development

  • Experience with financial APIs (Bloomberg, Refinitiv, IEX)

  • Background in quant environments or trading desks

  • Knowledge of CI/CD, observability, and automated testing

 
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