Senior Data Engineer — Quantitative Data Platform

Trexquant Investment; Connecticut; On-site; USD 150,000 - 200,000; Full time

Benefits offered by this job

Competitive salary plus bonus

Casual and friendly work environment

PPO health, dental, and vision保险 for你和

Pre-tax commuter benefits

Weekly company meals

Job summary

Trexquant is seeking an experienced Senior Data Engineer to build and maintain the core data infrastructure powering our quantitative research platform. You will own ingestion, normalization, storage, and ongoing maintenance of large-scale financial and alternative datasets from hundreds of global vendors.

You will design scalable data pipelines and collaborate with researchers, data architects, and infrastructure teams to ensure accurate, reliable, and accessible market, reference, and

Qualifications

• 5+ years of data engineering experience in a quantitative/financial tech setting.
• Strong Python and SQL development for large-scale ETL pipelines.
• Proficient Linux scripting, automation, and production data processing.
• Deep knowledge of financial data across asset classes and vendor feeds.

Responsibilities

• Design, build, and maintain scalable ingestion pipelines for market and alternative data.
• Own normalization, validation, storage, and lifecycle management of research datasets.
• Develop Python- and SQL-based data processing workflows for multiple asset classes.
• Collaborate with researchers, data architects, and infrastructure teams to onboard datasets.
• Build monitoring, automation, and tooling to ensure reliability and scalability of the data platform.
• Document data pipelines and best practices for Trexquant’s data infrastructure.

Skills

Python

SQL

Linux

Data pipelines

Collaborative skills

Education

Bachelor’s or Master’s in CS/Engineering/Math

Tools

Parquet

Arrow

Object storage

Columnar databases

Job description

Trexquant is seeking an experienced Senior Data Engineer to build and maintain the core data infrastructure powering our quantitative research platform. You will own ingestion, normalization, storage, and ongoing maintenance of large-scale financial and alternative datasets from hundreds of global vendors.

You will design scalable data pipelines and collaborate with researchers, data architects, and infrastructure teams to ensure accurate, reliable, and accessible market, reference, and