Senior Data Engineer: Finance Data Pipelines & Research

Jobtailor; Connecticut; On-site; USD 120,000 - 160,000; Full time

Job summary

Trexquant is seeking an experienced data engineer to design and maintain scalable ingestion pipelines for market, reference, tick, and vendor data. You will own data normalization, validation, storage, and lifecycle management to support quantitative research and simulations.

You will develop Python- and SQL-based workflows across equities, options, futures, fixed income, ETFs, and FX, collaborating with researchers and infra teams to onboard datasets and improve data quality.

Qualifications

• Bachelor’s or Master’s degree in computer science, engineering, mathematics, or related field.
• 5+ years of data engineering experience in quantitative or fintech environments.
• Proficient in Python and SQL for large-scale ETL pipelines.
• Strong Linux scripting and automation experience.
• Experience with market, reference, tick and vendor data feeds, and data quality control.
• Familiarity with Parquet, Arrow, object storage, and columnar databases.

Responsibilities

• Design, build, and maintain scalable data ingestion pipelines for multiple data types.
• Own normalization, validation, storage, and lifecycle management of research datasets.
• Develop Python- and SQL-based data processing workflows for various asset classes.
• Collaborate with researchers, data architects, and infra teams to onboard datasets.
• Build monitoring, automation, and tooling to ensure reliability and performance.

Skills

Python

SQL

Data pipelines

Linux scripting

Communication

Collaboration

ETL

Education

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

Tools

Parquet

Arrow

Object Storage

Columnar Databases

Job description

Trexquant is seeking an experienced data engineer to design and maintain scalable ingestion pipelines for market, reference, tick, and vendor data. You will own data normalization, validation, storage, and lifecycle management to support quantitative research and simulations.

You will develop Python- and SQL-based workflows across equities, options, futures, fixed income, ETFs, and FX, collaborating with researchers and infra teams to onboard datasets and improve data quality.