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Quantitative Data Engineer Jobs (NOW HIRING)

Quanta Search

Quant Data Engineer

Manhattan, NY

Our client, aglobalAsset Management firm, is looking for meticulous hands-on Quant Data Engineer provide historical and real-time bar data to Quant PMs for research and live strategies. Engineer will ...

Lazard, Inc.

Quantitative Data Analyst

Boston, MA · On-site

$90K - $150K/yr

The Advantage Quantitative Equity team is hiring a Quantitative Data Analyst to take ownership of ... developers to harden and operationalize your solutions * Maintain high-quality dataset ...

Lazard, Inc.

Quant Data Lead

Boston, MA · On-site

$200K - $240K/yr

... quantitative field. * 8-12+ years of experience in data engineering, data architecture, or ... quantitative data platforms. * 5+ years of experience using technologies such as Snowflake ...

Compunnel

Data Engineer

Jersey City, NJ · On-site

$119K - $143K/yr

... quantitative models for research, prediction, classification, and signal generation. • Apply ... data (feature engineering, model training, evaluation). • Build research and backtesting ...

HubAnalytics

Senior Quantitative Data Analyst

Cambridge, MA

$94K - $118K/yr

As a Quantitative Data Analyst, you'll design & implement marketing programs for a start-up company ... Engineering Degree Strong interest in Marketing Strong Statistical Insights and Logical Thinking ...

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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 24, 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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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.

Quant Data Engineer

Quanta Search

Manhattan, NY

Other

Posted 6 hours ago

Job description

Our client, aglobalAsset Management firm, is looking for meticulous hands-on Quant Data Engineer provide historical and real-time bar data to Quant PMs for research and live strategies. Engineer will provide the Quant Data API for historical and real-time Bars data used to analyze research data and for live trading. Candidate will work closely with the research PM to provide the data required for a given Strategy including validation of the data quality.
Requirements:
  • Past experience building Python data APIs
  • Experience writing data validations in Python
  • Systematic experience required
  • Keen sense of finding data issues.
  • Experience with one of the following required: Futures, FX or options market data
  • Past experience working with time series bars and real-time data.

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