DHTS IT ANALYST - QA Analyst

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About Duke Health Technology Solutions
Pursue your passion for caring and innovation with Duke Heath Technology Solutions, which is dedicated to the transformation, development, and management of enterprise information technology solutions across Duke Health. By harnessing the power of innovative technologies like cloud computing and artificial intelligence — and pairing them with a forward-thinking approach — Duke Health Technology Solutions is revolutionizing the future of health care at Duke Health and beyond.

POSITION DESCRIPTION
Job Title:  IT Analyst II (Data Quality Assurance Analyst)

DHTS: Duke Health Technology Solutions (DHTS) is a robust, specialized division of Duke University Health System dedicated to the development and management of enterprise IT systems. A 2018 ‘Most Wired’ health system, Duke is nationally recognized for IT and information management as the first healthcare system to achieve the Davies Award – the highest honor by the Healthcare Information and Management Systems Society (HIMSS) – for inpatient, ambulatory, and analytics health information technology capabilities. Duke was also the first to achieve Stage 7 HIMSS for Hospital EMR, Ambulatory EMR, and Analytics adoption. Our employees are among the top-skilled IT experts in the Triangle. We partner with leading scholars, clinicians, and researchers across Duke University and Duke Health to develop innovative technologies that support our mission of delivering tomorrow's healthcare today. 

Primary Role:  This position reports to the DHTS-Analytics Center of Excellence, Senior Manager, Data Engineering.  This individual will be primarily responsible for the quality of the FHIR-based content stored within Duke’s Enterprise Analytics Platform, in addition to providing quality assurance oversight of the data pipelines and REST APIs developed by the Data Engineering team.  The candidate should be an expert in data profiling, root cause analysis, and strategies to ensure the quality of data being delivered through big data and analytics platforms. The QA analyst will be a member of a Data Engineering Scrum team that is delivering 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. 

Essential Tasks/Responsibilities
•    Measure data quality - Design, collect, analyze, and report on data quality assurance/production performance metrics
•    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
•    Participate in the creation and maintenance of standards for coding, documentation, error handling, error notification, logging, etc. 

Education: Bachelor's degree in a related field, or four years of equivalent technical experience required

Required Experience:  We are looking for a candidate with 5+ years of experience in a Data QA Analyst role who has experience using and testing the following software/tools:
•    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.

Required Skills:
•    Expe