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Quantitative Data Engineer Jobs (NOW HIRING)

Edgestream

Data Engineer

Princeton, NJ · On-site

$120K - $144K/yr

... quantitative models of financial markets and deploying them in systematic trading strategies ... About the Job Edgestream is seeking a Data Engineer to build, scale and support our core data ...

Ford Motor Company

Data Engineer

Dearborn, MI · Hybrid

$115K - $192K/yr

Master's Degree in Computer Science, Data Engineering, or a related quantitative field. * 5+ years of professional Data Engineer experience * Strong SQL skills: Ability to write complex queries ...

Artius Solutions

Data Engineer

Dallas, TX · On-site

$60 - $65/hr

Bachelor's or Master's degree in Computer Science, Data Engineering, or a related quantitative field. * 7+ years of experience in data engineering, with at least 3+ years in a lead or senior role.

GridCARE

Data Engineer

Redwood City, CA · On-site

$140K - $168K/yr

Bachelor's or higher in Computer Science, Data Science, Electrical Engineering, or a related quantitative field. * Proficiency with cloud data platforms (e.g., AWS, GCP, Azure) and data warehousing ...

Central Intelligence Agency

Data Engineer

Washington, DC · On-site +1

$74K - $156K/yr

Summary DDI Data Engineers solve critical data challenges by building optimal data pipelines ... Data Science or related quantitative field * Information Science/Technology * Forensics (Digital ...

RIVIDIUM

Data Engineer

Quantico, VA · On-site

$123K - $148K/yr

RiVidium Inc. is seeking a Senior Data Engineer to support data-driven decision-making by ... related quantitative field * Equivalent work experience may be considered in lieu of a degree

Together For Talent

Data Engineer

Manhattan, NY · Hybrid

$150K - $300K/yr

Data Engineer | Early Hire Location: New York, NY (Hybrid) Salary: $150-300k Headquartered in New ... We've brought together top AI talent (from leading tech and quantitative firms) and experienced ...

Quanta Search

Market Data Engineer

Manhattan, NY

$126K - $151K/yr

Thisdivision offers an array of quantitative investment fund products to its clients. They are ... Researchers and developers there are passionate about their work, model building, data and ...

Analytica

Data Engineer

Washington, DC · On-site

$129K - $155K/yr

Bachelor's degree in Computer Science, Engineering, Information Technology, or a related quantitative field (or equivalent experience) * Experience working across cloud (AWS, Azure) or hybrid data ...

The New York Mets

Data Engineer

Queens, NY · On-site

$90K/yr

The New York Mets are seeking a Data Engineer for its Data Engineering Technology team. This role ... Support quantitative analysts in Baseball and Business Analytics with production deployments and ...

Analytica

Data Engineer

Washington, DC · On-site

$129K - $155K/yr

Bachelor's degree in Computer Science, Engineering, Information Technology, or a related quantitative field (or equivalent experience) * Experience working across cloud (AWS, Azure) or hybrid data ...

BUMBLE BEE FOODS, LLC

Data Engineer

San Diego, CA · On-site

$122K - $130K/yr

Bachelor's degree in computer science, Data Engineering, Information Systems, or a related quantitative field. * Job Requirementse design. * Proficiency in SQL for data transformation, validation ...

Bumble Bee Seafoods

Data Engineer

San Diego, CA · On-site

$122K - $130K/yr

Bachelor's degree in computer science, Data Engineering, Information Systems, or a related quantitative field. * Job Requirementse design. * Proficiency in SQL for data transformation, validation ...

BUMBLE BEE FOODS, LLC

Data Engineer

San Diego, CA · On-site

$122K - $130K/yr

Bachelor's degree in computer science, Data Engineering, Information Systems, or a related quantitative field. * Job Requirementse design. * Proficiency in SQL for data transformation, validation ...

Keylent Inc

Azure Data Engineer

Jersey City, NJ · On-site

$119K - $143K/yr

Data Engineer Design and develop technology solutions that meet the business requirements for ... Strong analytical, quantitative, problem solving, communication and organizational skills. Self ...

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Quantitative Data Engineer information

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$11K

$129.7K

$198K

How much do quantitative data engineer jobs pay per year?

As of Jun 25, 2026, the average yearly pay for quantitative data engineer in the United States is $129,666.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,500.00 and $138,500.00 per year, depending on experience, location, and employer.

What is an example of quantitative?

A quantitative example involves numerical data that can be measured and analyzed statistically. In a Quantitative Data Engineer role, this might include metrics like transaction volumes, data throughput, or statistical summaries used to build data pipelines and models.

What is quantitative vs qualitative?

Quantitative data refers to numerical information that can be measured and analyzed statistically, such as sales figures or sensor readings. Qualitative data involves descriptive, non-numerical information like opinions, interviews, or observations. In data engineering, understanding both types helps in designing systems that process and analyze diverse data sources effectively.

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 does quantitative mean?

In the context of a Quantitative Data Engineer role, 'quantitative' refers to working with numerical data and statistical methods to analyze and model information. This involves skills in mathematics, programming, and data analysis tools to develop algorithms and insights from large datasets.

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 are the synonyms of quantitative?

Synonyms of quantitative include numerical, measurable, and statistical. In a data engineering context, these terms relate to data that can be quantified and analyzed using tools like SQL, Python, or R, often involving numerical datasets and statistical methods.

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.
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What cities are hiring for Quantitative Data Engineer jobs? Cities with the most Quantitative Data Engineer job openings:
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What job categories do people searching Quantitative Data Engineer jobs look for? The top searched job categories for Quantitative Data Engineer jobs are:
Quantitative Data Engineer jobs near you
Infographic showing various Quantitative Data Engineer job openings in the United States as of June 2026, with employment types broken down into 1% Internship, 98% Full Time, and 1% Part Time. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $129,666 per year, or $62.3 per hour.
Data Engineer

Data Engineer

National Resident Matching Program

Washington, DC • On-site

$121K - $133K/yr

Full-time

Posted 5 days ago

Job description

About the Organization
The National Resident Matching Program® (NRMP®) is a private, not-for-profit organization established in 1952 to provide a uniform date of appointment to positions in graduate medical education (GME) in the United States. The NRMP is not an application processing service; rather, it provides an impartial venue for matching applicants' and programs' preferences for each other consistently. The NRMP conducts the annual Main Residency Match encompassing 40,000 applicants for more than 25,000 positions in core residencies as well as Matches for fellowship positions in 55 subspecialties through its Specialties Matching Service®.
POSITION SUMMARY
NRMP is looking to fill the full-time position of data engineer. The data engineer, , will play a pivotal role in operationalizing the data and analytics initiatives for NRMP. The data engineer will be building, managing, integrating, and optimizing reusable data pipelines and moving these data pipelines effectively into production for key data and analytics consumers - business/data analysts, research analysts, executives, and internal departments - that need curated data sets for data and analytics use cases.
The data engineer must support compliance with data governance and data security and privacy requirements to enable faster data access, integrated data reuse and vastly improved time-to-solution for NRMP data and analytics initiatives. The data engineer will be measured on their ability and agility to integrate analytics results with NRMP's business processes.
This role will be the key interface in operationalizing data and analytics on behalf of organizational outcomes and will require both creative and collaborative aspects- working with both IT and the wider business. The data engineer will also be tasked with working with key business stakeholders, IT experts and subject-matter experts to plan and deliver optimal analytics solutions.
ESSENTIAL DUTIES AND RESPONSIBILITIES
  • Build data pipelines: Managed data pipelines consist of a series of stages through which data flows from data sources of acquisition to integration to consumption for specific use cases. These data pipelines must be created, maintained, and optimized as workloads move from development to production for specific use cases. Architecting, creating, and maintaining data pipelines will be the primary responsibility of the data engineer.
  • Drive Automation through effective metadata management: The data engineer will be responsible for using innovative and modern tools, techniques, and architectures to partially or completely automate the most-common, repeatable and tedious data preparation and integration tasks in order to minimize manual and error-prone processes and improve productivity. The data engineer will also need to assist with renovating the data management infrastructure to drive automation in data integration and management.

This will include (but not be limited to):
  • Using modern data preparation, integration and metadata management tools and techniques.
  • Tracking data consumption patterns.
  • Monitoring schema changes.
  • Recommending and automating - existing and future integration flows.
  • Collaborate across departments: The newly hired data engineer will need strong collaboration skills to work with varied stakeholders within the organization. In particular, the data engineer will work in close relationship with research teams and with data analysts in refining their data requirements for various data and analytics initiatives and their data consumption requirements.
  • Become a data and analytics evangelist: The data engineer will be considered a blend of data and analytics "evangelist," "data guru" and "fixer." This role will promote the available data and analytics capabilities and expertise to business unit leaders and educate them in leveraging these capabilities in achieving their business goals.

EDUCATION, experience and general requirements
  • At least 6-8 years or more of work experience in data management disciplines including data integration, modeling, optimization, and data quality, and/or other areas directly relevant to data engineering responsibilities and tasks.
  • At least 3 years of experience working in cross-functional teams and collaborating with business stakeholders in support of departmental and/or multi-departmental data management, analytics, and business intelligence initiatives.
  • A bachelor's or master's degree in engineering or computer science or a related quantitative field.
  • AWS Certified Developer certification is highly desirable.
  • The ideal candidate will have a combination of IT skills, data governance skills, and analytics skills.
  • Familiarity with undergraduate and graduate medical education and the residency selection process is highly desirable.
  • Legal authorization to work in the United States without sponsorship or restriction.
  • Resides in the United States and ability to work remotely with occasional overnight travel.

TECHNICAL KNOWLEDGE AND SKILLS
  • Strong experience with Object-oriented/object function scripting using python and related libraries.
  • Strong experience with popular database programming languages including SQL and PL/SQL for relational databases.
  • Strong experience in working with and optimizing ETL/ELT processes and data integration / data preparation flows and moving them across various environments including production.
  • Proficient in working in AWS environment (Glue, S3, Lambda, IAM)
  • Experience in working with open-source technologies such as Airflow to automate data pipelines.
  • .
  • Adept in agile methodologies and capable of applying DevOps and increasingly DataOps principles to data pipelines to improve the communication, integration, reuse and automation of data flows between data providers and consumers across NRMP.
  • Ability to implement data quality checks and ensure data integrity within the data warehouse environment
  • Experience working with data quality, security, and governance teams in moving data pipelines through environments with appropriate data quality, governance and security standards.

INTERPERSONAL SKILLS AND CHARACTERISTICS
  • Be highly creative and collaborative. An ideal candidate would be expected to collaborate with cross functional teams to define the business problem, refine the requirements, and design and develop data deliverables accordingly.
  • Be a confident, energetic self-starter with strong interpersonal skills.
  • Comfortable in a fast-paced small company environment with the ability to manage a variety of projects simultaneously.
  • Have good judgment, demonstrate initiative, and demonstrate commitment to high standards of ethics, regulatory compliance, customer service, and business integrity.
  • Collaborate with Business Intelligence team to build effective solutions
  • Keen interest in learning and using latest software tools, methods and technologies to solve problems with an eye on maintainability.
  • Be a strategic, intellectually curious thinker with a focus on outcomes.

INTERACTIONS
External:
  • Frequent interaction with NRMP IT consultants and partners.
  • Periodic interaction with staff of other national health care organizations and researchers in academia.

Internal:
Frequent interaction with other NRMP staff in monitoring data warehouse, data pipelines, research and reporting environments
ADA SPECIFICATIONS
This position is primarily remote and sedentary; there may be infrequent overnight travel and duties may require some bending and lifting. The above statements describe the general nature and level of work being performed by the individual(s) assigned to this position. They are not an exhaustive list of all duties, responsibilities, and skills required.
NRMP is an equal opportunity employer and values diversity. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability or other protected class status. In addition, reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions of this position.

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