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Quantitative Data Engineer Jobs in Providence, RI

COMFORT SYSTEMS

Data Scientist I

Providence, RI · On-site

$61 - $123/hr

The role requires increasing technical expertise in the fields of computer programming, applied ... Bachelor's degree in quantitative field is preferred * 2 years preferred of professional experience ...

Apex Systems

Data Scientist-Agentic AI

Woonsocket, RI · On-site

Job#: 3040790 Data Scientist-Agentic AI Location: REMOTE Role Overview We are seeking a Senior Data ... Engineering, Physics, or a related quantitative field is required. Experience: 3+ years of ...

PPL Corporation

Product Manager

Providence, RI · Hybrid

Uses a qualitative and quantitative data driven approach to shape priorities and feature definition ... Work with engineering and design during discovery to identify and validate solutions to prioritized ...

SAIC

Systems Safety Engineer

Middletown, RI · On-site

Utilizing quantitative and qualitative risk assessment techniques to perform safety analysis in ... data, mishap investigation reports, safety test plans and results, and other ESOH related data.

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All JobsQuantitative Data Engineer JobsQuantitative Data Engineer Jobs in Providence, RI

Quantitative Data Engineer information

See Providence, RI salary details

$11.1K

$131K

$200K

How much do quantitative data engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for quantitative data engineer in Providence, RI is $130,993.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,700.00 and $139,900.00 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 are popular job titles related to Quantitative Data Engineer jobs in Providence, RI?

For Quantitative Data Engineer jobs in Providence, RI, the most frequently searched job titles are:

What job categories do people searching Quantitative Data Engineer jobs in Providence, RI look for?

The top searched job categories for Quantitative Data Engineer jobs in Providence, RI are:

Quantitative Data Engineer jobs near you
Infographic showing various Quantitative Data Engineer job openings in Providence, RI 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 $130,993 per year, or $63 per hour.

Executive Director, Data Engineering - Retail Analytics

CVS Health

Woonsocket, RI • On-site

$175K - $334K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 18 days ago

Key responsibilities

  • Define and execute the data engineering strategy that supports CVS Health's Retail analytics ecosystem.

  • Lead the design, building, and scaling of enterprise data platforms, AI products, and engineering capabilities.

  • Partner with Data Science, Product, Analytics, Architecture, and business stakeholders to deliver reliable, scalable, cloud-based data solutions.

CVS Health rating

5.8

Company rating: 5.8 out of 10

Based on 4,364 frontline employees who took The Breakroom Quiz

92nd of 113 rated pharmacies

Job description

We're building a world of health around every individual - shaping a more connected, convenient and compassionate health experience. At CVS Health, you'll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselvesaccountable and prioritize safety and quality in everything we do. Join us and be part of something bigger - helping to simplify health care one person, one family and one community at a time.

Position Summary

The Executive Director, Data Engineering serves as a senior technology leader within Analytics Engineering, responsible for defining and executing the data engineering strategy that powers CVS Health's Retail analytics ecosystem.

This role leads a large, multi-disciplinary engineering organization focused on designing, building, and scaling enterprise data platforms, AI products, and engineering capabilities that support Retail Pharmacy, Front Store, Retail Supply Chain, Merchandising, Personalization, Pricing, Marketing, and Operational analytics initiatives.

This leader partners closely with Data Science, Product, Analytics, Architecture, and business stakeholders to deliver reliable, scalable, cloud-based data solutions that accelerate insight generation and enable advanced analytics and AI-driven decision-making.

The Executive Director drives engineering excellence, talent development, platform modernization, and operational rigor while ensuring alignment with enterprise technology strategy and business priorities.

Required Qualifications:
  • 15+ years of progressive experience in Data Engineering, Software Engineering, Analytics Engineering, or related technology disciplines.
  • 7+ years of experience leading large engineering organizations through multiple layers of leadership.
  • Proven experience designing and delivering enterprise-scale data platforms, data products, and cloud-native engineering solutions.
  • Deep expertise in modern data engineering practices, including data pipelines, distributed processing, cloud platforms, data governance, and platform reliability.
  • Demonstrated success partnering with Analytics, Data Science, Product, and business organizations to translate complex business needs into scalable technology solutions.
  • Strong experience leading large transformation initiatives, platform modernization efforts, and organizational change.
  • Adept at execution and delivery, including strategic planning, roadmap development, and operational management.
  • Adept at business intelligence and data-driven decision making.
  • Mastery of collaboration, stakeholder management, and executive communication.
  • Mastery of problem solving, strategic thinking, and organizational leadership.
  • Mastery of growth mindset principles with a demonstrated ability to develop leaders and build high-performing teams.
Preferred Qualifications:
  • Experience supporting Retail, Pharmacy, Merchandising, Supply Chain, Marketing, Consumer, or Omnichannel analytics environments.
  • Experience building and scaling enterprise data products, feature stores, real-time data solutions, or analytics enablement platforms.
  • Strong knowledge of cloud-based data ecosystems, platform engineering, DevOps, DataOps, and engineering best practices.
  • Experience enabling AI, machine learning, and advanced analytics solutions through robust data engineering capabilities.
  • Experience operating within a highly regulated, large-scale enterprise environment.
  • Demonstrated ability to influence senior executives and drive alignment across complex organizational structures.
  • Track record of building engineering cultures centered on innovation, accountability, continuous improvement, and delivery excellence.
Education:

Bachelor's degree in Computer Science, Engineering, Information Systems, Mathematics, Statistics, or a related quantitative field required.

Master's degree in Computer Science, Engineering, Business Administration, Data Science, or a related discipline preferred.

Pay Range

The typical pay range for this role is:

$175,100.00 - $334,750.00


This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. This position also includes an award target in the company's equity award program.

Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.

Great benefits for great people

We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families.

This fulltime position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial wellbeing of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility.


Additional details about available benefits are provided during the application process and on Benefits Moments.

We anticipate the application window for this opening will close on: 09/18/2026

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.

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