1

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

The role collaborates with engineering, operations, supply chain, and affordability teams to ... quantitative data interpretation. Qualifications We Prefer * Active and transferrable Top ...

The ideal candidate has strong background in quantitative skills (like statistics, mathematics ... Learning new engineering practices, technologies and continuously improving our Agile practices ...

... of quantitative information and have a passion for high impact data storytelling. Essential ... Partner with the Data Engineering team to source, integrate, and validate data from across the Firm

... of quantitative information and have a passion for high impact data storytelling. Essential ... Partner with the Data Engineering team to source, integrate, and validate data from across the Firm

Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical Documentation * Technical ... Quantitative Analytics, or Data Analytics. * Experience producing or reviewing research papers ...

Showing results 41-60

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 Sep 3, 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 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.

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 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 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.

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:

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.

Manager, Data Analysis - PULSE Risk & Compliance

Capital One

Houston, TX • Hybrid

Full-time

Posted 5 days ago


Capital One rating

7.8

Company rating: 7.8 out of 10

Based on 148 frontline employees who took The Breakroom Quiz

88th of 174 rated banks


Job description

Manager, Data Analysis - PULSE Risk & Compliance

We are seeking a highly analytical, Manager Data Analysis to join our Data Strategy team. In this role as a Manager, Data Analysis, you will help build the framework and manipulate/analyze large datasets to understand PULSE transaction anomalies and risk exposure.

This is a hybrid role designed for someone who speaks the language of machine learning, data architecture, and modeling, but also deeply understands regulatory frameworks, risk controls, and compliance mandates.

You will be responsible for ensuring that our data-driven strategies are not only highly effective and scalable, but also ethical, explainable, and strictly compliant with industry regulations.

If you are a recovering data scientist who loves policy, or a risk and compliance manager who writes Python on the weekends, this is the role for you.

Responsibilities:

Design and implement a program for Transaction Monitoring aligned with Risk identification and modification. Build automated risk programs, isolate compromised data elements, and ensure the operational health and integrity of the PULSE network.

The "Translator": Act as the primary liaison between highly technical teams (Data Engineers, Data Scientists) and non-technical stakeholders (Legal, Compliance, Executive Board).

Risk Data Architecture: Partner with Data Engineering to design and optimize the architecture of risk data environments. Ensure data used for risk decisioning is accurate, accessible, and structured for advanced analytics. Strategic Advising: Advise product and business teams on the risk implications of new data strategies, alternative data sources, and emerging technologies

The payment ecosystem is constantly evolving, this role requires a unique blend of deep technical expertise, payment network knowledge, and sharp critical thinking to separate signal from noise.

What you'll do:

Drive current and future strategy by leveraging your analytical skills Data-Driven Investigations: Conduct root-cause analyses on transactions and translating complex data findings into actionable risk mitigation strategies.

Data Analytics: Advanced SQL, Python, Splunk, and data visualization for parsing high-volume transaction logs.

Executive Reporting: Synthesize highly technical data into clear, compelling narratives and present risk exposure, incident reports, and strategic recommendations to senior leadership.

Critical Thinking & Problem Solving: Proven ability to approach complex, ambiguous problems systematically. You must be able to deconstruct issues, challenge the status quo, and anticipate the downstream impacts of network changes.

On any given day you will be:

Working with large and complex databases containing millions to billions of records

Mining data to arrive at specific and crucial information for the organization

Identifying and implementing process, data, and reporting improvements for the organization

Conducting analysis to evaluate processes and tests

An ideal candidate will possess strong problem solving and conceptual thinking abilities. This position will be in a fast-paced and entrepreneurial environment where you will be handling multiple concurrent projects while working independently and in teams.

Basic Qualifications

  • Currently has, or is in the process of obtaining a:

    • Bachelor's Degree in quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science or a related quantitative field) plus at least 6 years of experience performing data analytics, or

    • Master's Degree plus at least 4 years of experience performing data analytics with an expectation that required degree will be obtained on or before the scheduled start date.

  • At least 4 years of experience performing professional data analysis work

  • At least 4 years of experience performing programming

Preferred Qualifications:

  • Master's Degree in a Science, Technology, Engineering, Mathematics discipline

  • At least 7 years of professional data analysis work experience

  • At least 4 years of experience with Python, R, Spark or SQL

  • At least 1 year of experience in people management

  • At least 1 years of project management experience

  • At least 1 year of experience in Tableau

  • Proficient utilizing and developing within AWS service

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Riverwoods, IL: $149,800 - $171,000 for Data Analysis Manager


Chicago, IL: $149,800 - $171,000 for Data Analysis Manager


Houston, TX: $149,800 - $171,000 for Data Analysis Manager









Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).


What Capital One employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom