
Data QA Test Engineer
2 weeks ago
Job Description Data QA Engineer (2–3 Years, Python + SQL + Cloud)
Position Overview
We are seeking a Data QA Engineer with 2–3 years of experience in Python, SQL, and cloud-based ETL/data testing. The role focuses on validating data pipelines, ensuring data quality, and building Python scripts for automation. Basic knowledge of ML and GenAI models is a plus.
Key Responsibilities
- Validate ETL processes in AWS, Azure, GCP, or Snowflake.
- Perform checks on schema, row counts, duplicates, nulls, and aggregates.
- Reconcile source and target datasets.
- Write SQL queries (joins, subqueries, CTEs, window functions) for testing.
- Perform performance checks and data consistency validation.
- Write validation scripts using pandas, numpy, sqlalchemy.
- Automate test cases with pytest or unittest.
- Validate data from cloud storage (S3, Blob, GCS) using Python SDKs.
- Apply data quality checks with frameworks like Great Expectations.
- Assist in validating ML workflows (data preparation, input/output checks).
- Work with Python libraries (scikit-learn, tensorflow) for basic model testing.
- Explore GenAI APIs (OpenAI, HuggingFace) for test data generation.
Required Skills
- 2–3 years of experience in data QA/testing.
- Strong knowledge of Python (pandas, numpy, pytest, sqlalchemy).
- Proficiency in SQL (joins, aggregates, window functions).
- Hands-on with at least one cloud platform (AWS, Azure, GCP, Snowflake, Databricks).
- Understanding of data quality checks (row counts, duplicates, transformations).
Good to Have
- Experience with ML/GenAI concepts and Python libraries.
- Familiarity with CI/CD tools (Jenkins, GitHub Actions, Azure DevOps).
- Knowledge of workflow tools like Airflow or Prefect.
- Basic API testing using Python (requests).
Qualifications
- Bachelor's in Computer Science, IT, or related field.
- 2–3 years of experience in ETL/Data QA with Python + SQL.
- Exposure to cloud platforms and data pipelines.
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