Data Quality Engineer
Posted 3
views
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.