Good-to-Have Skills:

Experience with data governance tools such as Apache Atlas, Collibra, or Alation
Understanding of DataOps methodologies and practices
Familiarity with monitoring/observability tools such as Datadog, Prometheus, or CloudWatch
Experience building or maintainingtest data generators
Contributions to internal quality dashboards or data observability systems
Awareness of metadata-driven testing approaches and lineage-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.

Test Automation Engineering Manager (Data Catalog)