What are the responsibilities and job description for the ETL QA Lead with Healthcare Client Exp - Minneapolis, MN (GC and USC only) position at Caliber Smart?
Position: Quality Assurance Analyst, Lead
Duration: 6 month CTH
Location: Local to Minneapolis onsite once/week
Key Responsibilities
Data Profiling and Assessment: Analyze data sources to understand their structure, content, and quality, identifying anomalies and patterns that may affect data integrity
Data Cleansing and Enrichment: Develop and implement processes to correct inaccuracies, remove redundancies, and fill in missing information to maintain high-quality datasets.
Data Quality Monitoring: Establish and monitor data quality metrics, creating dashboards and reports to track data quality trends and issues.
Root Cause Analysis: Investigate data quality problems to determine their origin and work with relevant teams to implement corrective measures
Process Improvement: Collaborate with cross-functional teams to enhance data collection, entry, and validation processes, thereby reducing the occurrence of data quality issues.
Data Governance: Contribute to the development and enforcement of data quality standards and policies, ensuring compliance with regulatory requirements
Source to Target testing , functional and integration testing
Preferred Tools
Quality automation tools . Query surge etc.
Best Regards,
Chetna
630-425-6471 -D
815-600-8657-Fax
Chetna@smartcaliber.com
www.smartcaliber.com
Truth Lies in Heart
Duration: 6 month CTH
Location: Local to Minneapolis onsite once/week
- ETL testing experience is a must have (Informatica is their ETL tool) with strong Oracle and SQL query writing experience. Good to have automation they do not have a tool they currently use, they used QuerySurge to maintain test cases and schedule automation.
- Healthcare experience required
Key Responsibilities
Data Profiling and Assessment: Analyze data sources to understand their structure, content, and quality, identifying anomalies and patterns that may affect data integrity
Data Cleansing and Enrichment: Develop and implement processes to correct inaccuracies, remove redundancies, and fill in missing information to maintain high-quality datasets.
Data Quality Monitoring: Establish and monitor data quality metrics, creating dashboards and reports to track data quality trends and issues.
Root Cause Analysis: Investigate data quality problems to determine their origin and work with relevant teams to implement corrective measures
Process Improvement: Collaborate with cross-functional teams to enhance data collection, entry, and validation processes, thereby reducing the occurrence of data quality issues.
Data Governance: Contribute to the development and enforcement of data quality standards and policies, ensuring compliance with regulatory requirements
Source to Target testing , functional and integration testing
Preferred Tools
Quality automation tools . Query surge etc.
Best Regards,
Chetna
630-425-6471 -D
815-600-8657-Fax
Chetna@smartcaliber.com
www.smartcaliber.com
Truth Lies in Heart
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