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Quantitative Data Engineer Jobs in Raleigh, NC (NOW HIRING)

Sennos

Sr ML/AI Engineer

Durham, NC · On-site

$101K - $138K/yr

This is a new role on a new team, evolving from existing data engineering and data science ... Bachelor's degree in Computer Science, Statistics, Mathematics, or related quantitative field ...

StratEdge It consulting INC

Business Analyst

Raleigh, NC · On-site

$50/hr

... data-rich exploratory analysis, build complex quantitative models, and deliver automated executive dashboards. Business Analysis & Requirements Engineering: Strong Business Analyst (BA) background ...

Clever Devices Ltd.

Product Specialist

Apex, NC · On-site

$70K - $120K/yr

Analyzes and correlates quantitative data to real event data * Prepares all materials to be needed ... Bachelor's Degree in engineering or equivalent, computer engineering, computer science or ...

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All JobsQuantitative Data Engineer JobsQuantitative Data Engineer Jobs in Raleigh, NC

Quantitative Data Engineer information

See Raleigh, NC salary details

$10.7K

$126K

$192.5K

How much do quantitative data engineer jobs pay per year?

As of Sep 11, 2026, the average yearly pay for quantitative data engineer in Raleigh, NC is $126,046.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,200.00 and $134,600.00 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 Raleigh, NC?

For Quantitative Data Engineer jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Quantitative Data Engineer jobs in Raleigh, NC look for?

The top searched job categories for Quantitative Data Engineer jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Quantitative Data Engineer jobs?

Cities near Raleigh, NC with the most Quantitative Data Engineer job openings:

Quantitative Data Engineer jobs near you

In Product Customer Experience Lead (Pendo)

Raleigh, NC • On-site

FREEDOM SOLUTIONS GR
See more jobs at FREEDOM SOLUTIONS GRexternal

Other

Medical, Retirement, PTO

Posted 10 days ago

Key responsibilities

  • Manage and optimize the global Pendo instance, including defining success metrics, establishing governance, and ensuring data integrity.

  • Analyze product usage data to identify friction points and design in‑app guides, walkthroughs, and resource centers to improve user onboarding and feature adoption.

  • Create dashboards and reports to track product adoption, retention, and engagement metrics for executive leadership.

Job description

Overview

As an In‑Product Customer Experience Lead (Pendo) at Litera, you will be part of a dynamic team that is passionate about driving innovation in the legal technology space. You will have the opportunity to work with cutting‑edge tools and collaborate with industry experts to deliver solutions that make a real difference in the legal profession.

Key Responsibilities
  • Pendo Center of Excellence Support: Drive best practice of the global Pendo instance, specifically around product adoption best practices. Define success metrics, establish governance and tagging best practices, and ensure data integrity across all Litera products.
  • Driving Adoption: Analyze product usage data to identify friction points. Design and deploy in‑app guides, walkthroughs, and resource centers that lead users to their "Aha!" moment faster.
  • Onboarding Orchestration: Facilitate a seamless transition for new users by building automated, personalized onboarding paths that reduce time‑to‑value.
  • Behavioral Insights: Serve as the "voice of the user" by providing qualitative and quantitative data to Product Managers and Engineering to influence the product roadmap.
  • Cross‑Functional Execution: Collaborate with Marketing, Sales, and Customer Success to ensure in‑app communications are aligned with the broader customer lifecycle.
What you will do
  • Pendo Administration: Manage user permissions, metadata mapping, segment creation, and subscription settings.
  • In‑App Strategy: Build and experiment with in‑app guides and polls to drive feature velocity and gather real‑time user feedback.
  • AI‑Driven Lifecycle: Lead the charge in integrating AI tools to personalize the user journey and automate support within the product.
  • Reporting & Analytics: Create dashboards for executive leadership that track Product Adoption Scores, retention trends, and guide engagement.
  • Governance: Manage the Product Development Lifecycle integration with Pendo, ensuring new features are "tagged and ready" before they launch.
Qualifications
  • Pndo Expertise: Extensive hands‑on experience as a Pendo Administrator (Pendo Certification is a plus).
  • The "Builder" Mindset: A track record of taking a tool and scaling it into a functional business process.
  • Technical Acumen: Deep understanding of how SaaS software works (HTML/CSS selectors for tagging is a must).
  • Analytical Curiosity: You don’t just report numbers; you find the "why" behind user behavior.
  • Collaboration: Proven ability to influence stakeholders across Product, Engineering, and Customer Success.
  • Education: Bachelor’s degree or equivalent professional experience in Digital CX, Product Ops, or Marketing Tech.
Benefits
  • Health insurance, retirement savings plans, generous paid time off, and a supportive work‑life balance.
  • Opportunities for professional development and career growth within the company.
Equal Opportunity Employer

Litera is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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