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Python Automation Testing Jobs in Katy, TX (NOW HIRING)

ComboCurve, Inc.

Senior Software Engineer, Python

Houston, TX · On-site +1

$117K - $154.20K/yr

Improve CI/CD pipelines, testing practices, and developer experience across the platform. * Partner ... platform automation and capabilities. * Shell Scripting: Competency in Bash scripting for ...

ESP Enterprises, Inc.

QA Testing Analyst

Houston, TX · On-site

$48 - $51/hr

Knowledge of programming or scripting languages like Java, Python, or JavaScript. * Certifications ... Knowledge of automation frameworks and scripting languages enhances the ability to create automated ...

CG Infinity

QA Lead

Houston, TX · On-site

Strong experience with Selenium, Java or Python, TestNG/JUnit, API testing, and CI/CD tools such as Jenkins. * Experience designing scalable automation frameworks and maintaining regression test ...

Noblesoft Technologies

Test Lead

Houston, TX · On-site

$45.25 - $61.75/hr

SQL, Postman, Cypress, Selenium, and automated API testing * TypeScript and C# (Python a plus) * Experience with creating automation framework and maintaining existing framework. * Azure and AWS ...

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How much do python automation testing jobs pay per hour?

As of May 31, 2026, the average hourly pay for python automation testing in Katy, TX is $47.05, according to ZipRecruiter salary data. Most workers in this role earn between $40.58 and $53.61 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Python Automation Testing professional, and why are they important?

To thrive as a Python Automation Testing professional, you need strong proficiency in Python programming, knowledge of software testing methodologies, and experience with test automation frameworks, often supported by a degree in computer science or a related field. Familiarity with tools such as Selenium, PyTest, Jenkins, and version control systems like Git is typically required, along with certifications like ISTQB being advantageous. Analytical thinking, attention to detail, and effective communication skills help testers identify issues, collaborate with teams, and document findings clearly. These competencies ensure the creation of reliable, maintainable automated tests that improve software quality and streamline development cycles.

What are some common challenges faced in a Python Automation Testing role, and how can they be addressed?

One common challenge in Python Automation Testing is maintaining test scripts as applications evolve, which can lead to flaky tests or outdated scripts. To address this, it's important to implement modular and reusable code, and regularly review and refactor test cases. Collaborating closely with developers and participating in code reviews can also help testers anticipate changes and adapt their tests proactively. Additionally, integrating robust reporting and logging mechanisms helps quickly identify and resolve issues, ensuring the reliability of the automated test suite.

What is Python Automation Testing?

Python Automation Testing refers to the process of using Python programming language to write scripts that automatically test software applications. These scripts can validate functionality, performance, and reliability of software, reducing the need for manual testing and speeding up the development cycle. Python is popular for automation testing because of its readability, extensive libraries like Selenium and PyTest, and strong community support. Automation tests can be integrated into continuous integration pipelines to ensure consistent quality across software releases.

What is the difference between Python Automation Testing vs Manual Software Testing?

AspectPython Automation TestingManual Software Testing
Required SkillsPython programming, automation tools, scriptingTest case execution, attention to detail, communication
Work EnvironmentAutomated testing frameworks, scripting environmentsTest labs, user environments, manual execution
Industry UsageSoftware development, QA teams, continuous integrationInitial testing phases, exploratory testing, user acceptance

Python Automation Testing involves writing scripts to automate test cases, increasing efficiency and repeatability. Manual Software Testing requires testers to execute test cases manually, focusing on exploratory and usability aspects. Both roles are essential in software quality assurance, but Python Automation Testing emphasizes automation skills, while manual testing emphasizes detailed test execution and observation.

What are popular job titles related to Python Automation Testing jobs in Katy, TX? For Python Automation Testing jobs in Katy, TX, the most frequently searched job titles are:
What job categories do people searching Python Automation Testing jobs in Katy, TX look for? The top searched job categories for Python Automation Testing jobs in Katy, TX are:
What cities near Katy, TX are hiring for Python Automation Testing jobs? Cities near Katy, TX with the most Python Automation Testing job openings:
Python Automation Testing jobs near you
Senior Software Engineer, Python

Senior Software Engineer, Python

ComboCurve, Inc.

Houston, TX • On-site, Remote

$117K - $154.20K/yr

Full-time

Posted 28 days ago

Job description

ComboCurve is a industry leading cloud-based software solution for A&D, reservoir management, and forecasting in the energy sector. Our platform empowers professionals to evaluate assets, optimize workflows, and manage reserves efficiently, all in one integrated environment.
By streamlining data integration and enhancing collaboration, we help operators, engineers, and financial teams make informed decisions faster. Trusted by top energy companies, ComboCurve delivers real-time analytics and exceptional user support, with a world-class customer experience team that responds to inquiries in under 5 minutes.
We're hiring a Senior Software Engineer to join our Platform Team. You'll help design and build the core services, internal APIs, and data workflows that power ComboCurve's products. This role is ideal for someone who loves writing modern Python, caring about architecture and testability, and building platform capabilities that make the rest of engineering faster and more reliable.
What You'll Do
  • Build and maintain robust platform services and internal tooling primarily in Python.
  • Design clean, well-typed interfaces and services that scale with growing data volumes and product needs.
  • Develop and own internal APIs that other teams depend on, with strong contracts and documentation.
  • Create high-performance data processing paths inside services to support analytics and ingestion workloads.
  • Deploy and operate Python services on GCP using serverless and managed platforms.
  • Improve CI/CD pipelines, testing practices, and developer experience across the platform.
  • Partner closely with product engineers, data engineers, and leadership to shape platform direction.
  • Write ADRs, architecture diagrams, and technical documentation that scale decision-making.
  • Mentor other engineers through code reviews, pairing, and pragmatic standards-setting.

Requirements
  • Advanced Python Proficiency: Deep expertise in Python 3.13+, specifically utilizing type annotations, async/await patterns, and modern language features to build robust platform services.
  • Modern Dependency Management: Hands-on experience with uv for fast package management (or similar), dependency resolution, and virtual environment handling.
  • Software Architecture Patterns: Strong adherence to SOLID principles and clean architecture; ability to design decoupled, maintainable systems that scale.
  • API Design & Development: Experience designing internal APIs using REST or gRPC, including defining clear, standard contracts using OpenAPI specifications.
  • High-Performance Data Processing: Experience using polars, PyArrow, or Apache Iceberg for efficient large-scale data manipulation and processing within application logic.
  • Data Warehouse Integration: Experience connecting Python applications to modern data platforms like Snowflake or Databricks for data ingestion and retrieval.
  • Google Cloud Platform: Proven track record deploying and managing services on GCP, specifically using Cloud Run, Cloud Functions, and Google Cloud Storage.
  • CI/CD: Ability to design and maintain pipelines for automated testing, linting, and cloud deployment; experience with GitHub Actions is strongly preferred.
  • Automated Testing Strategy: Extensive experience writing comprehensive test suites using pytest, including the use of fixtures, parameterization, and mocking external services.
  • Technical Leadership: Ability to mentor team members through code reviews, ADRs and architecture diagrams.
  • AI Agent Frameworks Experience: building or integrating with AI agent frameworks and LLM orchestration tools to enhance platform automation and capabilities.
  • Shell Scripting: Competency in Bash scripting for automating local developer tasks, build processes, or operational utility scripts.
  • Version Control Mastery: Deep understanding of Git, including branching strategies, conflict resolution, and maintaining a clean commit history.
  • Containerization: Proficiency in Docker and Docker Compose for creating consistent local development environments and production-ready images.
  • Static Analysis Configuration: Familiarity with enforcing code quality standards using ruff for linting and pyright for strict static type checking.

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