Key Responsibilities
• Perform detailed data validation between legacy production dataflows and new Databricks-based sources.
• Analyze and confirm accuracy of migrated data points and business logic.
• Test report functionality and ensure outputs align with expected business rules.
• Identify, document, and communicate data inconsistencies, defects, and root causes.
• Partner closely with IT and data engineering teams to resolve issues and track ticket progress.
• Provide regular written and verbal updates on validation progress, findings, and outstanding risks.
• Work independently as a self-starter, managing workload and timelines with minimal direction.
Qualifications
• Experience with data validation, QA, or analytical testing in a data engineering or reporting environment.
• Familiarity with data warehouses, ETL/dataflow testing, or Databricks preferred.
• Strong SQL and Excel skills; ability to compare datasets and troubleshoot discrepancies.
• Excellent communication skills, including summarizing findings for technical and non-technical audiences.
• High attention to detail and strong problem-solving mindset.
• Perform detailed data validation between legacy production dataflows and new Databricks-based sources.
• Analyze and confirm accuracy of migrated data points and business logic.
• Test report functionality and ensure outputs align with expected business rules.
• Identify, document, and communicate data inconsistencies, defects, and root causes.
• Partner closely with IT and data engineering teams to resolve issues and track ticket progress.
• Provide regular written and verbal updates on validation progress, findings, and outstanding risks.
• Work independently as a self-starter, managing workload and timelines with minimal direction.