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Quantitative Data Engineer Jobs in Houston, TX (NOW HIRING)

RIT Solutions, Inc.

Palantir Developer

Spring, TX · On-site

RIT Solutions, Inc. is seeking a Senior Data Engineer specializing in Python and Palantir to join ... Required : • Bachelor's degree in computer science, engineering, quantitative sciences, or ...

Invesco

Senior Engineer-1

Houston, TX · Hybrid

$99K - $137K/yr

  • Medical

  • Retirement

  • PTO

This role will partner closely with quantitative research teams, model owners, and downstream ... Ensuring data quality, completeness, and traceability through proper logging, monitoring, and ...

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All JobsQuantitative Data Engineer JobsQuantitative Data Engineer Jobs in Houston, TX

Quantitative Data Engineer information

See Houston, TX salary details

$10.5K

$123.8K

$189.1K

How much do quantitative data engineer jobs pay per year?

As of Aug 16, 2026, the average yearly pay for quantitative data engineer in Houston, TX is $123,828.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,300.00 and $132,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a quantitative data engineer, and why are they important?

To excel as a Quantitative Data Engineer, you need strong proficiency in programming (such as Python, R, or C++), advanced mathematical and statistical knowledge, and a relevant degree in computer science, mathematics, or a related field. Experience with big data tools (like Spark, Hadoop), cloud platforms, and data pipeline systems, as well as familiarity with financial data sets, is typically required. Analytical thinking, detail orientation, and effective problem-solving skills distinguish top performers in this role. These competencies are critical for efficiently transforming complex data into actionable insights and supporting robust quantitative models in data-driven environments.

What is a quantitative data engineer?

A Quantitative Data Engineer is a professional who designs, builds, and maintains data infrastructure that supports quantitative analysis, typically in finance or technology sectors. They work closely with quantitative analysts and data scientists to ensure efficient data pipelines, data quality, and high-performance systems for processing large datasets. Their responsibilities include developing ETL processes, optimizing databases, and implementing data models to support research and trading strategies. Strong programming skills, expertise in big data technologies, and knowledge of quantitative methods are essential for this role.

What is the difference between Quantitative Data Engineer vs Data Scientist?

AspectQuantitative Data EngineerData Scientist
Primary FocusBuilding data pipelines, data infrastructure, and ensuring data qualityAnalyzing data, creating models, and deriving insights
Skills & ToolsSQL, Python, Spark, ETL processes, data architectureStatistics, machine learning, Python/R, data visualization
CredentialsComputer science, engineering, or related degrees; certifications in data engineeringStatistics, data science, or related degrees; certifications in data analysis or machine learning
Work EnvironmentData engineering teams, data infrastructure projectsData analysis teams, research, and modeling projects

While both roles work closely with data, Quantitative Data Engineers focus on building and maintaining data systems, whereas Data Scientists analyze data to generate insights and models. They often collaborate but have distinct skill sets and responsibilities within data-driven organizations.

How does a quantitative data engineer typically collaborate with data scientists and quantitative analysts on projects?

Quantitative Data Engineers work closely with data scientists and quantitative analysts to design, build, and optimize data pipelines that support complex modeling and analytics. They are often responsible for ensuring data quality, scalability, and efficient data processing, enabling analysts to focus on developing models and extracting insights. Regular collaboration includes translating analytical requirements into technical solutions, troubleshooting data issues, and iterating on data infrastructure to support evolving project needs. This teamwork fosters an environment where technical and analytical expertise complement each other, leading to more robust and actionable results.

What are popular job titles related to Quantitative Data Engineer jobs in Houston, TX?

For Quantitative Data Engineer jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching Quantitative Data Engineer jobs in Houston, TX look for?

The top searched job categories for Quantitative Data Engineer jobs in Houston, TX are:

What cities near Houston, TX are hiring for Quantitative Data Engineer jobs?

Cities near Houston, TX with the most Quantitative Data Engineer job openings:

Quantitative Data Engineer jobs near you
Infographic showing various Quantitative Data Engineer job openings in Houston, TX as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $123,828 per year, or $59.5 per hour.

Quantitative Analyst, Gas & Power Trading

Trafigura

Houston, TX

Full-time

Re-posted 19 days ago

Job description

Main Purpose:The North America Quantitative Analysis team at Trafigura provides modeling and pricing support for our North America trading and origination activities, with a primary focus on U.S. power and gas.
We are seeking a highly motivated professional who aspires to excel in one of the leading global commodity trading organizations. Join us to contribute to our continued success in areas requiring quantitative expertise.Knowledge Skills and Abilities, Key Responsibilities:

Skills and Qualifications:

  • Advanced degree in mathematics, physics, finance, engineering, or computer science.

  • Prior experience supporting trading and origination activities.

  • In-depth knowledge and experience in financial mathematics, including option theory, derivative pricing, and risk analytics.

  • Working experience in building large-scale pricing model libraries in a team environment, utilizing software lifecycle collaboration tools such as GitLab or GitHub.

  • Development experience in object-oriented programming and design patterns.

  • Proficiency in coding with programming languages such as Python, C#, C++, and/or VBA.

  • Working knowledge of database applications, including Amazon Redshift, Oracle, and Snowflake.

  • Familiarity with web-based applications such as Streamlit or DASH.

  • Knowledge and experience with ETRM/CTRM systems like Allegro or Endur.

  • Competency in MS Office applications.

  • Strong verbal and written communication, and good interpersonal skills.

  • Minimum of 3-5 years of experience in similar roles within commodity trading, preferably in U.S. power and gas.

Key Responsibilities

  • Developing and maintaining proprietary valuation library and internal pricing tools.

  • Participating in and contributing to valuation requests for highly structured transactions.

  • Conducting bespoke analyses using historical and forward-looking data.

  • Bringing innovative solutions to ongoing modeling efforts.

  • Managing mission-critical databases.

  • Troubleshooting and enhancing existing data processes and analytics.

  • Documenting modeling approaches and methodologies.

Location

Houston, TX or Denver, CO

Key Relationships and Department Overview:

Reports into the Head of North America Quantitative Analysis, working closely with front office gas and power trading functions for North America.

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