Trexquant is seeking an experienced Senior Data Engineer to build and maintain the core data infrastructure that powers our quantitative research platform. This role is responsible for owning the ingestion, normalization, storage, and ongoing maintenance of large-scale financial and alternative datasets from hundreds of global vendors.The successful candidate will develop scalable data pipelines that transform raw vendor feeds into clean, consistent, research-ready datasets for systematic researchers and simulation platforms. Working closely with quantitative researchers, data platform engineers, and infrastructure teams, this person will ensure that market, reference, and alternative data is accurate, reliable, and readily accessible across asset classes including equities, options, futures, fixed income, ETFs, and foreign exchange.This is an ideal opportunity for an engineer who enjoys solving complex data engineering challenges in a research-driven environment where data quality, scalability, and performance directly impact alpha generation.ResponsibilitiesDesign, build, and maintain scalable ingestion pipelines for market, reference, tick, and alternative data from a diverse set of external vendors.Own the normalization, validation, storage, and lifecycle management of research datasets, ensuring data is accurate, consistent, and readily accessible for quantitative research and simulation.Develop and optimize Python- and SQL-based data processing workflows supporting multiple asset classes, including equities, options, futures, fixed income, ETFs, and FX.Partner with quantitative researchers, data architects, and infrastructure teams to onboard new datasets, improve data quality, and deliver reliable research-ready data.Build monitoring, automation, and operational tooling to ensure the reliability, performance, and scalability of the firm's data platform.Document data pipelines and engineering best practices while contributing to the ongoing evolution of Trexquant's research data infrastructure.RequirementsBachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related quantitative field.5+ years of data engineering experience within a systematic trading, quantitative research, hedge fund, or financial technology environment.Python and SQL development experience in building large-scale data ingestion and ETL pipelines.Strong Linux experience, including scripting, automation, and operating production data processing systems.Deep knowledge of financial data across multiple asset classes, including equities, options, futures, fixed income, ETFs, FX, and alternative datasets.Experience working with market data, tick data, reference data, and vendor data feeds, including normalization, validation, and quality control.Familiarity with modern data storage formats and technologies such as Parquet, Arrow, object storage, and columnar databases.Strong communication and collaboration skills, with the ability to work effectively alongside researchers and engineering teams.BenefitsCompetitive salary plus bonus based on individual and company performance.Collaborative, casual, and friendly work environment.PPO health, dental, and vision insurance premiums fully covered for you and your dependents.Pre-tax commuter benefits.Weekly company meals.Applications are open for both Stamford and New York City offices, the latter with a planned opening in September 2026.The base salary range is $150,000–$200,000, depending on the candidate's educational and professional background. Base salary is one component of Trexquant's total compensation, which may also include a discretionary, performance-based bonus. This position is classified as overtime-exempt.Trexquant is an Equal Opportunity Employer.
Trexquant is seeking an experienced Senior Data Engineer to build and maintain the core data infrastructure that powers our quantitative research platform. This role is responsible for owning the ingestion, normalization, storage, and ongoing maintenance of large-scale financial and alternative datasets from hundreds of global vendors.
The successful candidate will develop scalable data pipelines that transform raw vendor feeds into clean, consistent, research-ready datasets for systematic researchers and simulation platforms. Working closely with quantitative researchers, data platform engineers, and infrastructure teams, this person will ensure that market, reference, and alternative data is accurate, reliable, and readily accessible across asset classes including equities, options, futures, fixed income, ETFs, and foreign exchange.
This is an ideal opportunity for an engineer who enjoys solving complex data engineering challenges in a research-driven environment where data quality, scalability, and performance directly impact alpha generation.
Responsibilities
- Design, build, and maintain scalable ingestion pipelines for market, reference, tick, and alternative data from a diverse set of external vendors.
- Own the normalization, validation, storage, and lifecycle management of research datasets, ensuring data is accurate, consistent, and readily accessible for quantitative research and simulation.
- Develop and optimize Python- and SQL-based data processing workflows supporting multiple asset classes, including equities, options, futures, fixed income, ETFs, and FX.
- Partner with quantitative researchers, data architects, and infrastructure teams to onboard new datasets, improve data quality, and deliver reliable research-ready data.
- Build monitoring, automation, and operational tooling to ensure the reliability, performance, and scalability of the firm's data platform.
- Document data pipelines and engineering best practices while contributing to the ongoing evolution of Trexquant's research data infrastructure.
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related quantitative field.
- 5+ years of data engineering experience within a systematic trading, quantitative research, hedge fund, or financial technology environment.
- Python and SQL development experience in building large-scale data ingestion and ETL pipelines.
- Strong Linux experience, including scripting, automation, and operating production data processing systems.
- Deep knowledge of financial data across multiple asset classes, including equities, options, futures, fixed income, ETFs, FX, and alternative datasets.
- Experience working with market data, tick data, reference data, and vendor data feeds, including normalization, validation, and quality control.
- Familiarity with modern data storage formats and technologies such as Parquet, Arrow, object storage, and columnar databases.
- Strong communication and collaboration skills, with the ability to work effectively alongside researchers and engineering teams.
Benefits
- Competitive salary plus bonus based on individual and company performance.
- Collaborative, casual, and friendly work environment.
- PPO health, dental, and vision insurance premiums fully covered for you and your dependents.
- Pre-tax commuter benefits.
- Weekly company meals.
Applications are open for both Stamford and New York City offices, the latter with a planned opening in September 2026.
The base salary range is $150,000–$200,000, depending on the candidate's educational and professional background. Base salary is one component of Trexquant's total compensation, which may also include a discretionary, performance-based bonus. This position is classified as overtime-exempt.
Trexquant is an Equal Opportunity Employer.
Trexquant applies quantitative methods to systematically build optimized global market-neutral equity portfolios in liquid markets. Trading signals (Alphas) are developed from thousands of data variables and extensively tested. Strategies dynamically adjust allocations to Alphas depending on recent performance. Thousands of strategies using tens of thousands of signals currently drive our live production, and our talented team of researchers from some of the best schools in the world inject new ideas into our system on an ongoing basis. Capital is managed across thousands of equity positions in the United States, Europe, Japan, Australia, and Canada.
Trexquant applies quantitative methods to systematically build optimized global market-neutral equity portfolios in liquid markets. Trading signals (Alphas) are developed from thousands of data variables and extensively tested. Strategies dynamically adjust allocations to Alphas depending on recent performance. Thousands of strategies using tens of thousands of signals currently drive our live production, and our talented team of researchers from some of the best schools in the world inject new ideas into our system on an ongoing basis. Capital is managed across thousands of equity positions in the United States, Europe, Japan, Australia, and Canada.
