Only W2 -- Data QA Analyst

Data QA Analyst

100% Remote (EST Hours)

3+ Months CTH

Looking for a Data QA Analyst to join the Data Partnership team at one of our healthcare clients. The client is a large healthcare system located in North Carolina. To be successful in this role, the candidate should be an expert in data profiling, root cause analysis, and in creating strategies to ensure the quality of data being delivered through big data and analytics platforms. The QA analyst will deliver solutions focused on using state of the art data and analytics tools including traditional and near real-time data warehousing, big-data, relational and document-based databases using both extract, load, transform (ELT) toolsets as well as REST APIs and FHIR. The ideal candidate will be comfortable with data science platforms with proven experience leveraging DevOps and Test Automation tools.

Sr. Data QA Analyst Must Have Skills:

Experience with, and understanding of, implementing and measuring Data Quality and Controls

Testing data transformation, data structures, metadata, dependency, and workload management

Test automation and Azure DevOps integration

Extensive experience in Healthcare IT-clinical

Advanced working SQL knowledge and experience working with a variety of RDBMSs

Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement

Familiarity with Python development

API testing automation experience

Sr. Data QA Analyst Nice-to-Have Skills:

Azure Databricks experience

Experience with predictive modeling methods is a plus

Knowledge of open-source software solutions and open-source as a business model

Understanding of Agile and Scrum methodologies Working experience with the FHIR specification; including implementation

Working experience with the FHIR specification; including implementation

Sr. Data QA Analyst Responsibilities:
• Manage data quality documentation; define and maintain data standards, definitions, and models
• Identify incorrect data, documenting issues, patterns, and gaps in the data and/or systems
• Provide accurate and appropriate interpretation of data, applying knowledge for evaluation, analysis, and interpretation of data
• Ensure data integrity by implementing quality assurance practices
• Perform root cause analysis on data issues and recommend data quality controls to resolve gaps/issues
• Provide quality assurance oversight of data flows and APIs
• Contribute to agile story refinement and estimation
• Contribute as a member of the Data Engineering Scrum Team by developing and executing test cases during sprints to verify that the APIs and data pipelines developed meet defined acceptance criteria
• Collaborate with the Scrum Team and DevOps to automate test cases to be incorporated in the CI/CD pipelines
• Relational SQL and NoSQL databases, including Oracle, SQL Server, Postgres, and CosmosDB in Azure
• Data pipeline, workflow management, ETL tools such as Azure Data Factory, Synapse Pipelines
• The FHIR standard for healthcare data exchange
• Stream-processing systems such as NextGen Mirth or Spark-Streaming
• Object-oriented/object function scripting languages such as Python or Java
• Restful APIs and Web Applications
• Cloud-based analytic platforms such as Azure Synapse