Where you would value add

The role entails building a reusable sustainable framework to ensure collection, processing and availability of high-quality health care data to enable us to achieve the core purpose.  The Data Quality Engineer will work collaboratively with the Program Managers, Data Scientists, Data Architects and Data Engineers to ensure trustworthy data in development and in production.  Together these teams will enable automated metadata driven data quality frameworks proactively monitoring deviation in data quality and model outputs. The successful applicant will be working within a highly specialized and growing team to enable delivery of trustable data.

How you would make a difference

• Establish test criteria covering comprehensive monitoring of the accuracy of data that will be used for reporting, analytics, and machine learning
• Establish test criteria for reports and interactive dashboards
• Building a Test Plan that will be a living document reviewed at each phase and updated accordingly
• Review and finalization of the test plan to ensure accuracy of the methodology, test schedule and resource allocations
• Review the test cases and validate it against the requirement ensuring that all changes are implemented.
• Develop and review test scripts to validate it against the test case and ensure that all changes are implemented
• Review test results and validate this against the test scripts and ensure that all changes are
• implemented
• Ensure that all errors are logged, re-tested and closed.
• Manage feedback loop to all stakeholders of the project and development.
• Perform Regression Testing including lite testing to ensure there is no further impact on the system
• Keep all stakeholders informed regarding defects
• Produce a Test Closure Reporting summarizing activities that includes defects logged vs. Fixed, number of test cases executed etc.
• Mobilize sign off by client which includes Data Scientists and Business Users
• Monitor quality of productionized data sets, reports, dashboards and Model predictions
• Work with the Data Architect and Data Engineer to establish an automated framework to monitor production data assets
• Mentoring and Management of a QA team and driving their career development and training

What you need to be successful

• Honours degree in BSc Computer Science or Btech
• 5 to 15 years of experience is preferred
• Expert database knowledge in SQL and experience with MS Azure tools
• Strong numerical ability
• Strong data analysis capability
• Balancing of downstream assets against upstream data
• Modern Azure datawarehouse skills
• Metadata understanding in the context of ELT or ETL
• DevOps/DataOps and CI/CD experience
• Understanding of ML model process
• AWS experience
• Development background