Perform functional, integration, regression, and end-to-end testing for data and AI/ML applications. Validate data quality, transformations, ETL/ELT pipelines, model predictions, and data integrity using SQL and Python. Design test cases, automate testing, track defects, and collaborate with data engineers, data scientists, ML engineers, and development teams. Test model accuracy, performance, consistency, and reliability while supporting API, CI/CD, and data platform testing.
Role:
Data Quality Engineer
Experience:
3–7 Years
Location: Bengaluru
Notice Period: Immediate Joiners Preferred
Job
Description
We
are looking for an experienced Data / AI/ML Tester with 3–7 years of experience
in software testing, data validation, and AI/ML model testing. The ideal
candidate should have strong expertise in validating data pipelines, testing
machine learning models, and ensuring the accuracy, reliability, and quality of
AI-driven applications.
Key
Responsibilities
- Perform
functional, integration, regression, and end-to-end testing of Data and
AI/ML applications.
- Validate data
quality, data transformations, ETL/ELT pipelines, and data integrity.
- Test AI/ML models
for accuracy, performance, consistency, and reliability.
- Design and
execute test cases, test scenarios, and test scripts for data and ML
workflows.
- Perform SQL-based
data validation and backend testing.
- Validate model
predictions, outputs, and data processing results against expected
outcomes.
- Identify,
document, track, and report defects using defect management tools.
- Collaborate with
Data Engineers, Data Scientists, ML Engineers, and development teams.
- Support
automation testing for data pipelines and AI/ML applications.
Required
Skills
- 3–7 years of
experience in Data Testing, ETL Testing, AI/ML Testing, or Software
Testing.
- Strong SQL skills
for data validation and backend testing.
- Hands-on
experience with Python for test automation and data validation.
- Experience in
ETL/ELT testing and data quality validation.
- Understanding of
Machine Learning concepts, algorithms, and model evaluation metrics.
- Exposure to
testing AI/ML applications, predictive models, and data-driven solutions.
- Knowledge of API
testing using Postman or similar tools.
- Experience with
test management and defect tracking tools such as Jira.
- Familiarity with
cloud platforms (AWS, Azure, or GCP) and data platforms is an advantage.
Requirements
Preferred
Skills
- Experience with
PyTest, Selenium, or other automation frameworks.
- Exposure to
Databricks, Snowflake, Spark, or similar data technologies.
- Knowledge of
Generative AI, LLM testing, prompt validation, and response quality
testing is an added advantage.
- Understanding of
data pipeline orchestration and CI/CD testing.
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