Staff Data Platform Architect (Reliability & AI Readiness)

About This Role

The Staff Data Platform Architect will define, create, and drive the adoption of data reliability standards across Komodo Health, replacing fragmented quality metrics with a unified Data Reliability framework. This role involves strategic vision execution, prototyping, evangelism, and building technical frameworks to automate data reliability checks.

Responsibilities

• Lead the conceptual shift from general "data quality" to Data Reliability across the entire organization
• Design, prototype, and champion a single, centralized "Data Reliability Source of Truth" platform
• Create the technical framework and reference architecture to automate the creation, deployment, and monitoring of Data Reliability checks
• Serve as a strategic thought partner to the Head of Data Quality on all matters related to enterprise data reliability and quality assurance architecture
• Rapidly translate executive vision into tangible prototypes and scalable technical roadmaps
• Act as the Chief Evangelist for the Data Reliability metric, building conviction across executive, product, and engineering leadership
• Develop and lead change management programs to ensure seamless adoption of the new Data Reliability standard
• Define OKRs and KPIs for the Data Reliability initiative and deliver executive-level updates
• Formalize, package, and teach architectural and coding approaches for Data Reliability engineering
• Design the end-to-end architecture for the centralized Data Reliability Source of Truth
• Build and implement highly repeatable, configurable technical frameworks using Python/SQL/Spark to automate Data Reliability checks
• Drive the modeling and schema design of the core reliability tables
• Ensure defined Data Reliability metrics are fit-for-purpose for AI/ML models
• Provide technical coaching to existing Data Quality Engineers

Requirements

• 12+ years in Data Engineering, Data Architecture, or Platform Engineering with a focus on enterprise data quality/governance/testing
• 5+ years leading or designing enterprise-wide data quality frameworks
• Expert-level proficiency in SQL and Python
• Extensive experience designing and developing with distributed data processing platforms like Spark
• Experience with pipeline orchestration tools like Airflow
• Deep knowledge of modern cloud data warehousing environments (ideally Snowflake on AWS or similar MPP systems)
• Robust data modeling practices
• Practical experience ensuring data is prepared and validated for AI/ML model consumption
• "Evangelist" Mindset & Conviction: Leadership Presence, High Initiative, Persistence

Qualifications

• 12+ years of cumulative experience in Data Engineering, Data Architecture, or Platform Engineering, with a strong, dedicated focus on enterprise data quality/governance/testing. 5+ years of experience leading or designing enterprise-wide, multi-team data quality frameworks.

Skills

* Required skills

Benefits