Staff Data Quality Engineer, Komodo Health

• Experience: 10+ years of cumulative experience in Data Engineering, with a strong focus on data quality, testing data within a data warehouse, ODS, or analytics DB
• AI Focus: 3+ years of dedicated experience building for or building AI/ML products, specifically around data preparation, feature engineering, and ensuring data quality for model consumption
• Technical Mastery: Expert-level proficiency in SQL and Python for efficient and complex data manipulation, engineering, and testing
• Platform Expertise: Demonstrated proficiency in designing and developing with distributed data processing platforms like Spark and pipeline orchestration tools like Airflow
• Database & Modeling: Ability to use a variety of relational, NoSQL, Postgres, and/or MPP databases (ideally Snowflake on AWS) and leading data modeling, schema design, and data storage best practices
• Automation: Extensive prior experience performing both automated and manual data product validation, with a proven history of significantly increasing automation test coverage
• Communication: Proven ability to create, articulate, and present strategic, executive-level updates to technical and non-technical stakeholders

Desirable

• The Staff Data Quality Engineer will play a pivotal, enterprise-wide role in designing and implementing a unified, opinionated vision for data quality assurance and automation across Komodo's critical healthcare datasets
• This is a strategic and hands-on role focused on creating a single "source of truth" for QA that will directly inform our next-generation AI/ML product insights. You will be a technical leader, coaching junior team members and driving the modernization of our data quality infrastructure
• Essential Job Duties and Responsibilities (70% Focus: Execution & Building)
• Enterprise QA Automation: Design, build, and implement highly scalable, enterprise-wide QA automation infrastructure, creating a single, authoritative "source of truth" for data quality and testing
• AI/ML Integration: Leverage the existing data quality framework—or build a net-new system—to generate high-value insights for AI products, ensuring data is fit-for-purpose for machine learning models
• Data Quality Development: Build complex analytics pipelines and logic to address tangible data quality issues, assessing the completeness, consistency, and accuracy of complex data products
• Testing Framework & Coverage: Serve as the technical owner in developing and enhancing the product quality testing framework, driving a significant increase in overall automation test coverage. Write advanced automation SQL/Python scripts for comprehensive regression and functional testing
• Best Practices Evangelist: Collaborate with Data Engineers and ML Engineers across the organization to identify and bubble up "best of the best" architectural and coding approaches for data quality
• Mentorship & Coaching: Act as a technical coach and mentor to junior Data Quality Engineers, guiding them on efficient coding practices (SQL and Python) and advanced data quality engineering concepts
• Strategic and Executive Responsibilities (30% Focus: Strategy & Leadership)
• Strategic QA Vision: Be opinionated in defining how data quality problems should be solved and lead the strategic direction for data quality assurance, moving the team from consultative support to a prescriptive, best-practices-driven model
• Stakeholder Management: Proactively map out and engage necessary stakeholders and decision-makers (technical and business) across Komodo Health to drive alignment and adoption of enterprise QA standards
• Executive Updates: Take initiative to create and provide executive-level and strategic updates on the health of our data quality infrastructure, key quality trends, and the progress of strategic QA initiatives
• Product Ownership: Partner with Engineering and Product teams to own end-to-end quality processes for multiple data sources and products
• Reporting & Monitoring: Produce interactive, strategic data quality dashboards using off-the-shelf tools and Komodo applications to communicate data health and progress to a wide audience