Senior Automation Tester - PyTest / Databricks

Randstad
Irving, TX, United States
10 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$124,800.0 - $166,400.0
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Data Analysis Automation of Tests Microsoft Azure Big Data Code Coverage Continuous Integration Data Validation Extract Transform Load (ETL) Database Testing Github
+18 more
Python (Programming Language) Scrum Methodology Systems Development Life Cycle Mockito Standard Sql SQL Databases Test Data Test Management Strategies of Testing Performance Testing GitHub Copilot Pytest Data Lakes Pyspark Data Management Restful APIs Data Pipelines Databricks

Job description

Client is seeking a Senior Automation Tester to lead automated testing for Databricks-based data platforms. You will work with an existing Pytest framework, validate SQL-driven data pipelines moving into Databricks, and integrate automated tests into CI/CD pipelines via GitHub Actions. This role combines hands-on automation, data validation, and test management in qTest. Required Skills - PyTest, SQL, CI/CD, Databricks, GitHub Copilot Job Duties - Design, build, and maintain automated test suites using Python and Pytest - extending the existing Pytest framework already in place Validate data migrations and transformations from SQL to Databricks, including schema checks, row counts, data completeness, and business-rule validation Write and execute complex SQL queries in Databricks to verify ETL/ELT pipelines, Delta Lake tables, and downstream reporting data Integrate automated tests into CI/CD pipelines using GitHub Actions - triggering tests on pull requests, scheduled runs, and deployments, and reporting results back to the team Manage test cases, test plans, and defect traceability in qTest, linking automated results to manual test coverage Use AI-assisted tools such as Databricks Genie and GitHub Copilot to accelerate test creation, data exploration, and troubleshooting Partner with data engineers, developers, and product owners to define test strategies, acceptance criteria, and release readiness Mentor junior testers, review automation code, and drive best practices for test data, environments, and reporting Investigate failures, perform root-cause analysis, and raise/track defects through to resolution, Design, build, and maintain automated test suites using Python and Pytest - extending the existing Pytest framework already in place

Validate data migrations and transformations from SQL to Databricks, including schema checks, row counts, data completeness, and business-rule validation

Write and execute complex SQL queries in Databricks to verify ETL/ELT pipelines, Delta Lake tables, and downstream reporting data

Integrate automated tests into CI/CD pipelines using GitHub Actions - triggering tests on pull requests, scheduled runs, and deployments, and reporting results back to the team

Manage test cases, test plans, and defect traceability in qTest, linking automated results to manual test coverage

Use AI-assisted tools such as Databricks Genie and GitHub Copilot to accelerate test creation, data exploration, and troubleshooting

Partner with data engineers, developers, and product owners to define test strategies, acceptance criteria, and release readiness

Mentor junior testers, review automation code, and drive best practices for test data, environments, and reporting

Investigate failures, perform root-cause analysis, and raise/track defects through to resolution

Requirements

10+ years of QA / test automation experience, with 5+ years in a senior or lead role Strong hands-on experience with Python and Pytest for API and data testing Expert-level SQL skills, with proven experience validating data in Databricks (Databricks SQL, notebooks, Delta Lake, Unity Catalog a plus) Experience testing data pipelines, ETL processes, and large-scale data migrations Hands-on experience building and maintaining CI/CD pipelines, specifically GitHub Actions Experience with qTest or a similar test management tool integrated with automation Familiarity with AI tools such as Databricks Genie and GitHub Copilot Solid understanding of Agile/Scrum, SDLC, and defect lifecycle Strong communication skills, API,AI-assisted tools,AI tools,automated testing,automated tests,large-scale data,test coverage,data exploration,Delta Lake,data platforms,test data management,data pipelines,ELT pipelines,data validation,validating data,data testing,Databricks,Databricks SQL,ETL,ETL processes,GitHub Copilot,GitHub Actions,Azure,mocking,performance testing,PySpark,Pytest,Python,REST API,SQL,SQL queries,Agile/Scrum,SQL skills,test strategies,SDLC,test data,test management,Strong communication skills,acceptance criteria,Automation,automation experience,track defects,healthcare,Mentor,QA / test,Investigate,root-cause analysis,test management tool,test plans,testing

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