The Opportunity at Komodo Health

Quality is at the heart of everything that Komodo Health does. It is embedded in our vision — reduce the global impact of disease — and the mandate we have as a data and insight provider to leading global healthcare companies. The Data Product Quality team’s mission is to define, build, monitor, and improve the quality of Komodo’s Data Products.

Our data quality scientists help build analytics pipelines and complex logic for complicated data projects that solve tangible data quality issues. You will design, maintain, and implement data quality assurance processes, including understanding product requirement documents and transforming them into data quality assurance components. Typical tasks include, but not limited to performing complex data analysis and assessing completeness, consistency and accuracy of data products, writing automation SQL/scripts for regression testing, writing SQL/Scripts for functional testing, and producing interactive data quality dashboards

Looking back on your first 12 months at Komodo Health, you will have…

• Became an expert with our healthcare datasets especially Komodo’s healthcare MAP
• Effectively partnered with customer-facing teams to reconcile client requirements with the data quality capabilities of KH
• Incorporated a good understanding of the healthcare datasets at Komodo and client use-cases to effectively partner with data engineering teams for data quality decisions
• Partnered with Engineering and Product to own end to end quality processes for multiple sources
• Developed and enhanced our product quality testing framework and increased overall test coverage
• Developed quality monitoring tools based on advanced algorithms and modeling

What you bring to Komodo Health:

• Keenly analytical mindset and the ability to solve complex problems with limited supervision
• Experience writing SQL queries and working with Relational Databases AND/OR Proficient in scripting with Python
• Ability to work well both independently and collaboratively, in a fast-paced and agile environment
• Worked with testing data within a data warehouse, ODS or analytics DB
• Performed both automated and manual data product validation, with the focus on increasing automation test coverage
• Comfortable with version control systems such as Git/GitHub

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