
04/09/2025) Test Automation Engineering Manager
5 days ago
Good-to-Have Skills:
- Experience with data governance tools such asApache Atlas,Collibra, orAlation
- Understanding ofDataOpsmethodologies and practices
- Familiarity withmonitoring/observability toolssuch asDatadog,Prometheus, orCloudWatch
- Experience building or maintainingtest data generators
- Contributions tointernal quality dashboardsordata observability systems
- Awareness ofmetadata-driven testing approachesandlineage-based validations
- Experience working with agile Testing methodologies such as Scaled Agile.
- Familiarity with automated testing frameworks like Selenium, JUnit, TestNG, or PyTest.
Must-Have Skills:
- Strong hands-on experience with Data Quality (DQ) framework design and automation
- Expertise in PySpark, Python, and SQL for data validations
- Solid understanding of ETL/ELT pipeline testing in Databricks or Apache Spark environments
- Experience validating structured and semi-structured data formats (e.g., Parquet, JSON, Avro)
- Deep familiarity with AWS data services: S3, Glue, Athena, Lake Formation, Data Catalog
- Integration of test automation with AWS Glue Data Catalog or similar catalog tools
- UI automation using Selenium with Python for dashboard and web interface validation
- API testing using Postman, Python, or custom API test scripts
- Hands-on testing of BI tools such as Tableau, Power BI, Looker, or custom visualization layers
- CI/CD test integration with tools like Jenkins, GitHub Actions, or GitLab CI
- Familiarity with containerized environments (e.g., Docker, AWS ECS/EKS)
- Knowledge of data classification, access control validation, and PII/PHI tagging
- Understanding of data governance standards (e.g., GDPR, HIPAA, CCPA)
- Understanding Data Structures: Knowledge of various data structures and their applications.
- Ability to analyze data and identify inconsistencies.
- Proven hands-on experience in test automation and data automation using Databricks and AWS.
- Strong knowledge of Data Integrity Frameworks (DIF) and Data Quality (DQ) principles.
- Familiarity with automated testing frameworks like Selenium, JUnit, TestNG, or PyTest.
- Strong understanding of data transformation techniques and logic.
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