Data Quality Engineer at Evnek Technologies – Bangalore | Jobyssey

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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Requirements