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How much do pytest jobs pay per hour?

As of May 30, 2026, the average hourly pay for pytest in Decatur, GA is $33.04, according to ZipRecruiter salary data. Most workers in this role earn between $21.35 and $43.89 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Pytest Automation Engineer, and why are they important?

To excel as a Pytest Automation Engineer, you need strong programming skills in Python, a solid understanding of software testing principles, and experience with test automation frameworks. Familiarity with Pytest, continuous integration tools (like Jenkins), and version control systems (such as Git) is typically required, along with relevant certifications in software testing or Python development. Attention to detail, analytical thinking, and effective communication help you identify issues quickly and collaborate across development teams. These abilities are crucial for ensuring software quality, speeding up release cycles, and maintaining robust, scalable test systems.

How does a Pytest automation engineer typically collaborate with developers and QA teams during a software release cycle?

As a Pytest automation engineer, you will often work closely with both developers and QA professionals throughout the software release cycle. You’ll be responsible for creating and maintaining test suites using Pytest, reviewing code changes, and ensuring that automated tests cover new features or bug fixes. Regular communication is essential, as you’ll need to report test results, discuss defects, and coordinate on test coverage or continuous integration setup. This collaborative approach helps maintain high code quality and smooth releases.

What is Pytest and what is it used for?

Pytest is a popular testing framework for Python that allows developers to write simple as well as scalable test cases. It is widely used for unit testing, functional testing, and integration testing in Python projects. Pytest makes it easy to write small tests, yet it scales to support complex functional testing for applications and libraries. Its rich plugin architecture and simple syntax make it a preferred choice for many Python developers.

What is the difference between Pytest vs Selenium Tester?

AspectPytestSelenium Tester
Primary FocusAutomated testing framework for Python codeWeb application testing using browser automation
Required SkillsPython programming, testing frameworksWeb technologies, Selenium WebDriver, scripting
Work EnvironmentSoftware development, QA teams, CI/CD pipelinesWeb testing, QA teams, browser environments
Common CertificationsPython certifications, testing certificationsSelenium certifications, QA certifications

Pytest is a Python testing framework used primarily for unit and integration testing of Python applications. Selenium Tester specializes in automating web browsers to test web applications. While both roles involve testing, Pytest focuses on code-level testing within Python projects, whereas Selenium Testers focus on browser-based testing of web interfaces. Understanding these differences helps teams assign the right tools and skills for their testing needs.

What are popular job titles related to Pytest jobs in Decatur, GA? For Pytest jobs in Decatur, GA, the most frequently searched job titles are:
What job categories do people searching Pytest jobs in Decatur, GA look for? The top searched job categories for Pytest jobs in Decatur, GA are:
What cities near Decatur, GA are hiring for Pytest jobs? Cities near Decatur, GA with the most Pytest job openings:
Pytest jobs near you
Director, QA (Mortgage Data and AI)

Director, QA (Mortgage Data and AI)

Intercontinental Exchange Holdings, Inc.

Atlanta, GA

Full-time

Posted yesterday

Job description

Overview

Job Purpose

The QA testing is the department responsible for the Quality Assurance and delivery of high-quality data and products. 

We are seeking an experienced Director of QA for Mortgage Data and AI to lead our comprehensive quality assurance strategy for our mortgage data and artificial intelligence platforms. This is a strategic leadership role responsible for ensuring the highest standards of data integrity, system reliability, and AI model performance across our mortgage technology ecosystem. The ideal candidate will combine deep expertise in QA methodologies with knowledge of mortgage industry requirements, data validation, and AI/ML systems testing.

Responsibilities

  • Lead and manage a team of QA engineers, test automation specialists, and data quality analysts across multiple mortgage data and AI initiatives
  • Develop and implement comprehensive QA strategy and testing frameworks for mortgage data pipelines, ensuring 99.95%+ data accuracy and compliance
  • Establish quality standards and best practices for AI/ML model validation, including performance testing, bias detection, and edge case analysis
  • Oversee end-to-end testing of mortgage products including loan origination systems, pricing engines, risk assessment models, and data analytics platforms
  • Partner with engineering, product, and business teams to define quality requirements, acceptance criteria, and success metrics for all mortgage data and AI initiatives
  • Design and deploy automated testing solutions for data ingestion pipelines, ETL processes, and real-time mortgage data processing systems
  • Establish data governance and quality assurance processes to ensure compliance with regulatory requirements (MISMO, FNMA, FHLMC, GNMA standards)
  • Lead risk assessment and mitigation strategies for mortgage AI systems, including model drift detection, fairness auditing, and regulatory compliance validation
  • Manage QA budget, resource allocation, and vendor relationships for testing tools and infrastructure
  • Drive continuous improvement initiatives to reduce defect escape rate, improve test coverage, and accelerate time-to-market
  • Establish metrics and KPIs for QA team performance and provide regular reporting to executive leadership
  • Mentor and develop QA team members, fostering a culture of quality and continuous learning

Knowledge and Experience

  • Bachelor's degree in computer science, Software Engineering, Information Technology, or related field
  • 12+ years of QA experience, with at least 5 years in a leadership/management role
  • Proven experience managing QA teams and driving organizational quality standards
  • Deep understanding of mortgage industry, loan processes, and mortgage technology ecosystem
  • Strong background in data quality assurance, data validation, and ETL testing
  • Experience with AI/ML systems testing, model validation, and performance evaluation
  • Expertise in test automation frameworks, continuous integration/continuous deployment (CI/CD) pipelines
  • Proficiency in programming languages (Java, Python, C#, JavaScript) for test automation
  • Knowledge of API testing, database testing, and performance/load testing tools
  • Understanding of regulatory compliance requirements in financial services (FNMA, FHLMC, SEC, CFPB regulations)
  • Strong analytical and problem-solving skills with attention to detail
  • Excellent communication and stakeholder management abilities
  • Test Automation: Selenium, UFT/QTP, TestComplete, Cucumber, Robot Framework
  • Programming Languages: Java, Python, C#, JavaScript, SQL
  • Testing Tools: JIRA, TestRail, LoadRunner, JMeter, Postman, SoapUI
  • CI/CD Tools: Jenkins, GitLab CI, Azure DevOps, GitHub Actions
  • Databases: SQL Server, Oracle, PostgreSQL, MongoDB, data validation techniques
  • API Testing: RESTful APIs, SOAP, GraphQL, OAuth/security testing
  • Data Testing: ETL validation, data profiling, data quality tools
  • Cloud Platforms: AWS, Azure, Google Cloud Platform
  • AI/ML Testing: Model validation tools, performance metrics, bias detection frameworks

Preferred Knowledge and Experience

  • MBA or advanced degree in related field
  • ISTQB Certified Test Manager or equivalent QA certification
  • Experience with mortgage-specific platforms and systems (pricing engines, AUS systems, LOS)
  • Knowledge of machine learning algorithms and model evaluation techniques
  • Experience with data warehousing and big data testing (Hadoop, Spark, Cloud platforms)
  • Familiarity with Agile/Scrum methodologies and DevOps practices
  • Experience with open-source testing frameworks (Selenium, TestNG, JUnit, pytest)
  • Background in building quality assurance centers of excellence
  • Experience with test data management and synthetic data generation
  • Knowledge of financial regulations and compliance testing requirements

Core Competencies

  • Strategic Leadership & Visioning
  • Team Building and Talent Development
  • Process Improvement and Continuous Optimization
  • Risk Management and Compliance
  • Stakeholder Management and Communication
  • Technical Expertise and Problem-Solving
  • Data-Driven Decision Making
  • Agile & DevOps mindset
  • Change Management
  • Cross-functional Collaboration

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----------Intercontinental Exchange, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to legally protected characteristics.Employment Type: FULL_TIME

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