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 Mid-level Data Architect 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
• 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