Key Responsibilities

Design, develop, and execute data validation for large-scale data pipelines
Collaborate with data teams to understand data flow and transformations
Schema validation (types, nullability, constraints)
Anomaly/outlier detection (statistical thresholds, freshness checks)
Regression testing on transformation logic after schema/pipeline changes
Contribute to AI-assisted QA initiatives

Skills

1-2 years of experience in Data QA.
Strong hands-on expertise in SQL (tools to mention).Working knowledge of Cloud Systems (AWS, GCP etc).
Working knowledge of Python for scripting, data manipulation, and automation integration
Experience with orchestration or logging tools (like Airflow, Dagster, Cloudwatch etc.) enough to trace failures
Exposure of AI Tools
Familiarity with CI/CD tools (Jenkins, GitHub)
Solid analytical mindset, attention to detail, and ability to troubleshoot complex data issues.
Good to have understanding of DSP or AdTech data models

Skills: sql,qa,github,python,api testing,jenkins,aws,airflow,cloudwatch,ai tools,gcp

📌 Data QA Analyst I (Ahmedabad)
🏢 Rekruton Global IT Services
📍 Ahmedabad