Data Architect, Komodo Health

• 7+ years of experience in data architecture or data engineering roles, with expertise in Snowflake and Databricks
• Proficiency in designing and maintaining ETL workflows using Airflow or similar orchestration tools
• Strong understanding of access control models and their implementation in data systems
• Experience developing tagging frameworks for data classification, ownership, and cost tracking
• Strong familiarity with cloud environments (AWS preferred) and infrastructure as code (e.g., Terraform)
• Experience deploying and managing containerized data pipelines and analytics applications on Kubernetes, ensuring scalability, high availability, and integration with cloud platforms
• Proven ability to design and implement automation to reduce manual work and improve infrastructure efficiency
• Strong problem-solving and communication skills, with a focus on collaboration and driving innovation

Desirable

• The Data Infrastructure team at Komodo designs, builds, and maintains the foundational systems that power our data ecosystem
• This includes managing JupyterHub for data exploration, Airflow for orchestrating workflows, Snowflake for scalable data warehousing, and Databricks for advanced analytics and machine learning
• The team ensures these tools are reliable, scalable, and secure to meet the needs of our engineers, data scientists, and analysts
• This role exists to architect and optimize Komodo’s data infrastructure to enable seamless data access, processing, and analysis
• The Data Architect III will enhance the reliability, performance, and scalability of our systems, ensuring they meet the demands of a rapidly evolving healthcare data landscape while adhering to best practices for security and compliance
• Looking back on your first 12 months at Komodo Health, you will have accomplished…
• Architect and design a standardized access model across all data storage solutions to improve consistency and scalability
• Develop and implement a tagging structure to attribute ownership, sensitivity, and costs effectively across data infrastructure
• Design and deploy automation to reduce manual infrastructure provisioning and maintenance
• Implement optimizations to reduce overall data infrastructure costs by at least 15%
• Document data usage standards, approved tools, and best practices for internal stakeholders
• Test and promote the adoption of new tools for analytics and data storage to improve operational efficiency and innovation
• Architect and oversee the implementation of a unified access control model for all data storage solutions
• Develop tagging structures to classify data by ownership, sensitivity, and cost, ensuring alignment with compliance and reporting requirements
• Create automated solutions for provisioning, scaling, and maintaining data infrastructure
• Collaborate with the Operations and Engineering teams to identify and implement cost-saving measures
• Maintain and evolve documentation on data usage, tools, and infrastructure standards
• Evaluate and introduce innovative tools for data storage and analytics, conducting proofs of concept and recommending adoption paths
• Providing support to customers who encounter issues with db or query performance