Data Analysts / QA

📋 Description

• Hybrid QA Data Engineer role for data pipelines.
• Focus on data quality, testing, and validation.
• Collaborate with Data Engineering and Analytics teams.
• Ensure production readiness of data assets.
• Validate data accuracy across pipelines.
• Document data lineage across multiple domains.

🎯 Requirements

• 3+ years in Data Quality, QA, or Data Analysis.
• Expert SQL for data validation and analysis.
• Hands-on with data quality frameworks (Great Expectations preferred).
• Strong Python for data validation, automation, or analysis.
• Experience with data profiling, reconciliation, and validation.
• Experience building test automation for data pipelines.

🎁 Benefits

• Certifications in AWS, Databricks, Snowflake.
• Udemy Business access for courses.
• AI learning paths and study plans.
• English lessons for professional communication.
• Travel to industry conferences.
• Mentoring and development programs.