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

Jobtailor

Data Scientist

Raleigh, NC · On-site

$110 - $170/hr

Bachelor's degree or equivalent in Statistics, Applied Mathematics, Physics, Engineering, Data Science, or a related quantitative field. * 3+ years of experience (with Bachelor's), 2+ years of ...

Western Governors University

Decision Scientist

Raleigh, NC · On-site

$118K - $178K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Bachelor's degree in a quantitative field such as Computer Science, Data Science, Statistics, Engineering, Behavioral Sciences, or related discipline. Experience * 5+ years of experience in data ...

Western Governors University

Decision Scientist

Raleigh, NC

$118K - $178K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Bachelor's degree in a quantitative field such as Computer Science, Data Science, Statistics, Engineering, Behavioral Sciences, or related discipline. Experience * 5+ years of experience in data ...

Trilon Group

Civic Data Analyst (Sustainable Mobility)

Durham, NC · On-site

$65K - $76K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... Engineering with some experience in the software development and/or data science fields. * Proficiency in Python and/or R, SQL * Proficiency in Quantitative Analysis: A solid background in data ...

Trilon

Civic Data Analyst (Sustainable Mobility)

Durham, NC · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... Engineering with some experience in the software development and/or data science fields. * Proficiency in Python and/or R, SQL * Proficiency in Quantitative Analysis: A solid background in data ...

Capgemini

Data Scientist

Cary, NC · On-site

$85.79 - $97.27/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative field.* 8+ years of experience in Data Science, Machine Learning ...

Kyndryl

Data Analyst

Durham, NC · On-site

  • Medical

  • Dental

  • Retirement

  • PTO

... quantitative discipline, such as industrial engineering, finance, or economics • Knowledge of data analysis tools and programming languages (e.g. Looker, Power BI, QuickSight, BigQuery, Azure ...

Kyndryl

Data Analyst

Durham, NC · On-site

  • Medical

  • Dental

  • Retirement

  • PTO

Degree in a quantitative discipline, such as industrial engineering, finance, or economics Knowledge of data analysis tools and programming languages (e.g. Looker, Power BI, QuickSight, BigQuery ...

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Showing results 21-40

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 Aug 19, 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

Data Scientist

Jobtailor

Raleigh, NC • On-site

$110 - $170/hr

Other

Posted 13 days ago

Job description

  • Design and implement statistical and machine learning models for time-series forecasting, anomaly detection, and asset health scoring across utility networks.
  • Build and maintain end-to-end ML pipelines on Databricks from feature engineering and model training to validation, deployment, and monitoring in production.
  • Apply classical statistical methods (GLMs, GAMs, mixed-effects models, Bayesian inference) alongside modern ML techniques (ensemble approaches, network analysis, neural networks) to solve grid operations problems.
  • Develop predictive maintenance and degradation models for utility infrastructure using telemetry and SCADA data at scale.
  • Translate ambiguous business problems into well-defined modeling problems with appropriate statistical frameworks - e.g., knowing when a LM/GLM is sufficient and when gradient boosting or deep learning is warranted.
  • Implement model monitoring, drift detection, and automated retraining workflows to maintain model performance over time.
  • Contribute to load forecasting, demand response optimization, and outage prediction systems.
  • Ensure model interpretability and explainability for utility stakeholders and regulatory compliance.
  • Contribute to internal knowledge-sharing on statistical best practices.
Requirements
  • Bachelor’s degree or equivalent in Statistics, Applied Mathematics, Physics, Engineering, Data Science, or a related quantitative field.
  • 3+ years of experience (with Bachelor’s), 2+ years of experience (with Masters), or 1+ years (with PhD) in applied statistical modeling and machine learning, with a track record of deployed production models.
  • Strong programming skills in Python (PySpark, pandas, NumPy, scikit-learn, statsmodels, XGBoost), R (tidyverse, lme4, glmmTMB, glmnet, mgcv), and SQL for large-scale data analysis.
  • Experience with time-series modeling (ARIMA, state-space models, LSTM, Darts, or similar) on high-volume meter data.
  • Exposure to Databricks ML ecosystem (Feature Store, Experiment Track, Model Serving, Mosaic AI) and MLflow.
  • Familiarity with distributed computing concepts - PySpark, Optuna/Ray, Spark SQL, partitioning strategies, and medallion architecture.
  • Understanding of software engineering principles - version control (Git), testing, CI/CD for ML systems.
  • Ability to communicate complex statistical/ML concepts to non-technical stakeholders.
Core Competencies

Demonstrates expertise in statistical modeling and machine learning for time-series forecasting and anomaly detection, with a strong focus on building and maintaining ML pipelines and ensuring model performance and interpretability. Proficient in translating business problems into statistical frameworks and communicating complex concepts to stakeholders.

Highest-signal resume keywords
  • Statistical Modeling
  • Machine Learning
  • Python Programming
  • Time-Series Modeling
  • Databricks ML Ecosystem
ATS Optimization KeywordsHard Skills
  • Statistical Methods
  • Machine Learning Techniques
  • Feature Engineering
  • Model Training
  • Model Validation
  • Model Deployment
  • Model Monitoring
  • Anomaly Detection
  • Predictive Maintenance
  • Data Analysis
Soft Skills
  • Communication
  • Problem-Solving
Industry Keywords
  • Utility Networks
  • Telemetry Data
  • SCADA Data
  • Regulatory Compliance
  • Grid Operations
Tools & Technologies
  • Databricks
  • PySpark
  • SQL
  • MLflow
  • Git
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