Cookies & analytics consent
We serve candidates globally, so we only activate Google Tag Manager and other analytics after you opt in. This keeps us aligned with GDPR/UK DPA, ePrivacy, LGPD, and similar rules. Essential features still run without analytics cookies.
Read how we use data in our Privacy Policy and Terms of Service.
🤖 15+ AI Agents working for you. Find jobs, score and update resumes, cover letter, interview questions, missing keywords, and lots more.

Luxoft • India
Role & seniority: Senior QA Engineer (5+ years QA Automation)
Stack/tools: Databricks (DBRX), Python, PySpark, SQL; Azure DevOps; backend/API testing (REST); ETL/data warehouse context; PowerBI for dashboards
Automate data quality checks for Databricks, Data Lake, and Big Data environments; develop/maintain Data Quality and Data Expectation checks
Create and maintain test plans for the Data Market Hub platform; validate data integrity and support data processing workflows via SQL/PySpark
Collaborate with data engineers/platform teams; participate in requirements refinement; contribute to test reporting, dashboarding, and incident management
5+ years QA Automation; 3+ years testing big data on Databricks
Strong SQL and Python; solid PySpark experience
Hands-on with Azure DevOps; backend/API testing and data validation; experience with test automation tools
Familiarity with data warehouses/ETL tools; understanding of CI/CD
Location: Bangalore, Pune, Chennai, Hyderabad
Work type: Full-time role (location-based; remote/hybrid arrangements not specified)
We are seeking a Senior QA Engineer to ensure the stability, accuracy, and reliability of our Databricks-based data platforms. This role will primarily focus on validating and monitoring data pipelines, ETL processes, and backend data workflows within our Data Lake and Big Data environments. You will be responsible for implementing automated data quality checks, validating Databricks jobs regularly, and ensuring data integrity across the Data Market Hub platform. The position involves hands-on testing of data transformations using Python, PySpark, and SQL, executing pipeline validation checks, and supporting release cycles through structured QA processes. You will work closely with data engineers and platform teams to proactively identify issues, validate data accuracy, and maintain consistent quality standards across all data assets. Additionally, you will contribute to test reporting, dashboarding, and continuous improvement of QA practices within the data platform ecosystem.
Open for locations: Bangalore, Pune, Chennai, Hyderabad
RESPONSIBILITIES
Automate data quality checks for Databricks (DBRX), Data Lake, and Big Data environments.
Create and maintain test plans for the Data Market Hub platform.
Develop and maintain Data Quality and Data Expectation checks within the Market Data Hub Platform using Python/PySpark
Participate in requirements refinement and specification.
Use SQL to validate data integrity and support efficient data processing workflows.
Collaborate in the incident management process to ensure swift issue resolution.
Test Data Management: Use SQL to manage test data, retrieve relevant test information, and store test execution results in a centralized database for historical analysis and reporting.
Dashboard Design: Create PowerBI dashboards to provide insights into test results, code coverage, and performance trends across projects and test levels.
REQUIREMENTS
Minimum 5 years in QA Automation.
minimum 3 years of experience testing big data on the Databricks platform.
Strong knowledge of SQL and Python for creating test scripts.
Solid understanding of PySpark (3y+).
Hands-on experience with Azure DevOps.
Hands-on experience with backend and API testing, including REST services, authentication, and data validation
Experience with test automation tools.
Familiarity with data warehouses and ETL tools for quality testing.
Understanding of CI/CD processes and integration.
Fast learner with the ability to adapt to new technologies and tools.