Posted:1 month ago|
Platform:
Work from Office
Full Time
Must Have
1. 3+ years of experience in QA or Quality Engineering roles in data-driven environments.
2. Analyze the data requirements from Source to Target Mapping requirements
3. Hands-on experience with test automation frameworks (e.g., PyTest, Great Expectations, dbt tests).
4. Proficient in SQL for validating data transformations across platforms like Redshift, Postgres, or Snowflake.
5. Familiarity with ETL testing, data ingestion pipelines, and data quality validation techniques.
6. Experience testing and validating BI dashboards and reports, preferably using tools like Tableau.
7. Exposure to CI/CD practices and integration of tests into deployment pipelines.
8. Ability to read and write test cases in Python or other scripting languages.
9. Experience with version control tools (e.g., Git) and JIRA or similar test tracking systems.
1. Experience testing unstructured data pipelines, including logs, PDF documents, or application telemetry.
2. Familiarity with data profiling and anomaly detection tools.
3. Exposure to cloud platforms, especially AWS (S3, Redshift, Glue).
4. Understanding of analytical data modeling concepts, including Star Schema and OLAP structures.
5. Knowledge of testing AI/ML models, particularly for consistency, fairness, or accuracy in predictions.
Tata Consultancy Services
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