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Quantitative Data Engineer (Market Data)

Amtex System Inc.Morristown, NJ🇺🇸United StatesPosted 2 Sept 2026

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Morristown, NJ, United States
Posted
23 hours ago
SQLSQL ServerETLPythonREST

Job Description

Amtex Systems Inc is an information technology and talent solutions company offering talent and BI consulting to the companies in US for over 25 years.

Our solutions are designed to fill resource gaps, by providing the right candidates who deliver value to the organization. Our propensity to nurture and build strong relationships with our clients helps us better understand their business demands and gives us the ability to provide services that are on time and rise above the rest.


Job Title: Quantitative Data Engineer (Market Data)

Job Location: Morristown, NJ

Work Model: Hybrid (Tuesday, Wednesday, and Thursday on-site)

Project Duration: Permanent / Full-Time

Mode of Interview: Video / In Person

Must Have Skills:

  • MS or PhD in Computer Science, Engineering, Statistics, or a related discipline with excellent academic credentials.
  • 3+ years of production-level development experience in Python.
  • Proficiency in SQL, stored procedures, and database concepts (preferably with Microsoft SQL Server).
  • Familiarity with financial equity data, specifically Bloomberg, LSEG, Compustat, and CapIQ
  • Demonstrated experience in processing large and complex datasets.
  • Advanced knowledge of math, statistics, and strong problem-solving capabilities.

Position Overview:

We are seeking a Quantitative Data Engineer to join our team. You will research, design, code, test, and deploy models while supporting daily trading operations and collaborating directly with portfolio management and quantitative research teams.

Key Responsibilities:

  • Implement, enhance, and manage quantitative models for equity markets, frequently partnering with quantitative researchers on innovative ideas.
  • Design and improve proprietary data repositories and advanced financial data platforms.
  • Automate and support Extract, Transform, and Load (ETL) processes sourced from various market data vendors.

 

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