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Quantitative Data Engineer Jobs in Philadelphia, PA

ResolveSoft Inc

Be Seen First

Data Analyst

Philadelphia, PA · On-site

$65K - $85K/yr

This role conducts both quantitative and qualitative analyses, develops repeatable and sustainable ... The Data Analyst works closely with the Data Engineer/Data Project Lead, Data Visualization ...

Tech Impact

Data Engineer Fellowship

Wilmington, DE · On-site

$40/hr

Data Innovation Lab Data Engineer Fellowship * Join an innovative, like-minded team that focuses on ... another related quantitative field . However, undergraduates or individuals who have relevant ...

Deloitte

Generative AI Data Engineer III

Philadelphia, PA · On-site

$115K - $138K/yr

Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative field * 5+ years of professional experience * 3+ years of experience designing ...

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All JobsQuantitative Data Engineer JobsQuantitative Data Engineer Jobs in Philadelphia, PA

Quantitative Data Engineer information

See Philadelphia, PA salary details

$11.1K

$130.8K

$199.8K

How much do quantitative data engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for quantitative data engineer in Philadelphia, PA is $130,844.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,600.00 and $139,800.00 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 Philadelphia, PA?

For Quantitative Data Engineer jobs in Philadelphia, PA, the most frequently searched job titles are:

What job categories do people searching Quantitative Data Engineer jobs in Philadelphia, PA look for?

The top searched job categories for Quantitative Data Engineer jobs in Philadelphia, PA are:

Quantitative Data Engineer jobs near you
Infographic showing various Quantitative Data Engineer job openings in Philadelphia, PA as of July 2026, with employment types broken down into 1% As Needed, 78% Full Time, 13% Part Time, and 8% Contract. Highlights an 81% Physical, 3% Hybrid, and 16% Remote job distribution, with an average salary of $130,844 per year, or $62.9 per hour.

Quantitative/Data Developer | Fixed Income | Experienced Hire

Susquehanna International Group, LLP

Philadelphia, PA • On-site

Full-time

Re-posted 11 days ago

Job description

Overview
Susquehanna is seeking a Quantitative Developer with experience in Python to join our Fixed Income Technology Team.
This team focuses primarily on trading interfaces and technologies to empower the sales desk. You'll work alongside traders, quant analysts, and other technology teams to create, maintain, and enhance our proprietary trading systems.
In this role, you will:
  • Design and create proprietary software to handle mission critical trading demands, including but not limited to market data, quoting, pricing, risk, and P&L.
  • Work closely with traders and analysts to understand and iterate on requirements.
  • Work closely with various technology teams to deliver efficient and scalable solutions in a fast paced environment, which directly impacts production systems.

What we're looking for
  • At least 3 years of experience developing data tools and applications in Python is required.
  • Experience with the Python data science stack: NumPy, Pandas etc. and/or other array-oriented programming environments.
  • Prior experience in a Quant Developer role, with the ability to understand financial models and mathematical algorithms, preferred.
  • Strong interpersonal and communication skills for interacting with traders, quantitative analysts, and other software developers is required.
  • Interest in areas such as capital markets, probability, game theory and the application of IT solutions to these areas is a plus.
  • Minimum Bachelor's degree in CS, applied science, or similar preferred, advanced degree a plus.

About Susquehanna
Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.
If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.
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