Principal Software QA Engineer

Job Duties

The Senior Software QA Engineer is responsible for ensuring the accuracy, reliability, and quality of E&P data, applications, and workflows. The role focuses on working with subsurface and drilling domains, cloud based deployments, automation, and containerized environments. This position requires strong domain knowledge and hands on technical capability, with the ability to work independently and collaborate across multidisciplinary teams.

Key Responsibilities

•    Perform QA for Landmark applications, ensuring data integrity and workflow consistency
•    Validate subsurface, drilling, and production datasets for completeness, accuracy, and compliance
•    Develop and maintain automated QA scripts using scripts and other automation tools.
•    Support cloud based E&P application deployments on AWS and Azure
•    Build, test and validate Docker images and container configurations
•    Deploy and troubleshoot Kubernetes workloads for E&P applications
•    Participate in CI/CD processes, automated testing, documentation updates and release validation
•    Conduct root cause analysis for data or application quality issues
•    Collaborate with subsurface, drilling, IT and DevOps teams to ensure digital workflows meet quality standards
•    Document QA processes, test cases, and validation results
•    Ensure compliance with API, ISO and internal quality standards
•    Provide technical QA insights during system upgrades, migrations, and new tool deployments
•    Ability to use AI tools to bring efficiency to the testing

Required Technical Competencies

•    Strong hands on experience with OpenWorks, Petrel and Landmark EDT applications.
•    Deep understanding of E&P data types: seismic, well logs, drilling data, production data
•    Proficiency in Linux and Windows scripting (Bash, PowerShell, Python)
•    Experience with AWS and Azure cloud services (compute, storage, IAM, networking)
•    Strong working knowledge of Docker and container lifecycle management
•    Experience deploying and troubleshooting Kubernetes clusters
•    Familiarity with Git, CI/CD pipelines, and automated testing frameworks
•    Understanding of data governance, lineage, and quality rules for subsurface and drilling datasets