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Quantitative Software Developer Jobs in Texas (NOW HIRING)

Programmers.io

Snowflake Developer

Dallas, TX · On-site

... Engineering, or a related quantitative field. b. c. d. * Experience: Minimum of 3-5 years of ... Deep familiarity with the full Software Development Life Cycle (SDLC) and CI/CD best practices ...

Expand Energy

Quantitative Risk Analyst

Spring, TX · On-site

Additional programming capability in one or more of SQL, C#, C++, VBA, or similar languages ... Familiarity with Git/GitHub/GitLab, software lifecycle controls, and documentation standards is ...

Expand Energy

Quantitative Risk Analyst

Spring, TX

Additional programming capability in one or more of SQL, C#, C++, VBA, or similar languages ... Familiarity with Git/GitHub/GitLab, software lifecycle controls, and documentation standards is ...

Citadel

$4.5K - $5.8K/wk

At Citadel, Quantitative Research Engineers work closely with Quantitative Researchers to develop and implement automated trading system software solutions. These solutions utilize advanced ...

Expand Energy

Quantitative Risk Manager

Spring, TX

Additional programming capability in one or more of SQL, C#, C++, VBA, or similar languages ... Familiarity with Git/GitHub/GitLab, software lifecycle controls, and documentation standards is ...

Expand Energy

Quantitative Risk Manager

Spring, TX · On-site

Additional programming capability in one or more of SQL, C#, C++, VBA, or similar languages ... Familiarity with Git/GitHub/GitLab, software lifecycle controls, and documentation standards is ...

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Quantitative Software Developer information

What is a quantitative software developer?

A Quantitative Software Developer is a professional who combines expertise in software engineering, mathematics, and finance to design, develop, and maintain systems that support quantitative analysis and trading. They work closely with quantitative analysts (quants) to implement complex financial models, optimize trading strategies, and process large datasets efficiently. Their role often involves using programming languages like Python, C++, or Java to build low-latency, high-performance applications for financial institutions such as banks, hedge funds, or trading firms. The position requires a strong background in computer science, familiarity with financial markets, and the ability to solve challenging technical problems.

What are the key skills and qualifications needed to thrive as a quantitative software developer?

To thrive as a Quantitative Software Developer, you need strong programming skills (often in Python, C++, or Java), a solid foundation in mathematics and statistics, and typically a degree in computer science, mathematics, engineering, or a related field. Familiarity with numerical libraries, data analysis tools, version control systems, and experience with financial modeling platforms are highly valuable. Analytical thinking, problem-solving abilities, and effective communication help you collaborate with cross-functional teams and interpret complex data. These skills are crucial for building robust quantitative models and software that drive data-driven decisions in finance and technology sectors.

How do quantitative software developers typically collaborate with quantitative analysts and traders?

Quantitative Software Developers work closely with quantitative analysts and traders to translate complex financial models into robust, production-ready code. This collaboration often involves regular meetings to discuss model requirements, performance optimization, and real-time data integration. Developers may also pair with analysts to validate outputs and ensure accuracy, while providing technical expertise on software architecture and best coding practices. Strong communication and teamwork skills are vital for successfully bridging the gap between quantitative research and practical trading solutions.

What is the difference between Quantitative Software Developer vs Quantitative Analyst?

AspectQuantitative Software DeveloperQuantitative Analyst
CredentialsDegree in Computer Science, Software Engineering, or related fieldsDegree in Finance, Economics, or Mathematics
Work EnvironmentDevelops trading algorithms, risk systems, and data infrastructureAnalyzes financial data, models market behavior, and advises on investment strategies
Employer & Industry UsageFinancial firms, hedge funds, trading desksInvestment banks, asset management firms, hedge funds
Common Search & ComparisonFocuses on software development skills and codingFocuses on financial modeling and data analysis

While both roles operate within the finance industry, a Quantitative Software Developer primarily focuses on building and maintaining software systems used for trading and risk management. In contrast, a Quantitative Analyst concentrates on analyzing financial data and developing models to inform investment decisions. Understanding these differences helps candidates target their skills and career goals effectively.

Are quantitative software developers in demand?

Quantitative software developers are in high demand due to their expertise in programming, data analysis, and financial modeling, especially in finance, technology, and data-driven industries. Their skills in languages like Python, C++, and knowledge of algorithms make them valuable for developing trading systems, risk management tools, and analytics platforms, leading to strong job growth prospects.
Quantitative Software Developer jobs near you
Infographic showing various Quantitative Software Developer job openings in Texas as of September 2026, with employment types broken down into 89% Full Time, and 11% Contract. Highlights an 100% In-person job distribution.

Snowflake Developer

Dallas, TX • On-site

Programmers.io
IT Services • 501 - 1,000 employees
Learn more about Programmers.ioexternal

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

  • Bachelor’s or Masters in Computer Science, Applied Mathematics, Engineering, or a related quantitative field. b. c. d.
  • Experience: Minimum of 3-5 years of professional "hands-on-keyboard" coding experience in a collaborative, team-based environment.
  • Ability to trouble shoot (SQL) and basic scripting experience. Languages: Professional proficiency in Python or Java.
  • Methodology: Deep familiarity with the full Software Development Life Cycle (SDLC) and CI/CD best practices & K8s deployment experience.

2. Core Data Engineering Competencies:

  • Candidates must demonstrate a sophisticated understanding of the following modeling concepts to ensure data correctness during reconciliation:
  • Temporal Data Modeling: Managing state changes over time (e.g., SCD Type 2). b. c. d. Schema Management:
  • Expertise in Schema Evolution (Ref: Iceberg Apache) and enforcement strategies. Performance Optimization:
  • Advanced knowledge of data partitioning and clustering. Architectural Theory: Balancing Normalization vs. Denormalization and the strategic use of Natural vs. Surrogate Keys.

3.Technical Stack Requirements:

  • While candidates are not expected to be experts in every tool, the collective team must cover the following technologies:
  • Extraction & Logic Kafka, ANSI SQL, FTP, Apache Spark Data Formats JSON, Avro, Parquet Platforms Hadoop (HDFS/Hive), Snowflake, Apache Iceberg, Sybase IQ