Data Engineer, Komodo Health

• Expertise in writing enterprise-level code and contributing to large data pipelining and API processing with Python
• Experience with SQL and query design on large, complex datasets
• 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
• Demonstrated proficiency in designing and developing with distributed data processing platforms like Spark and pipeline orchestration tools like Airflow
• A thirst for knowledge, willingness to learn, and a growth-oriented mindset
• Committed to fostering an inclusive environment where your teammates feel motivated to succeed
• Excellent cross-team communication and collaboration skills

Desirable

• Reporting directly to the Engineering Manager, you will be solving complex data challenges while designing and implementing data processing and transformation at a scale that powers state-of-the-art interactive product experiences
• You will enable smarter, more innovative uses of healthcare data by building robust data pipelines and implementing data best practices
• Partnering with Engineering team members, Product Managers, Data Scientists, and customer-facing teams to understand complex health data use cases and business logic
• Being curious about our data
• Building foundational pieces of our data platform architecture, pipelines, analytics, and services underlying our platform
• Architecting and developing reliable data pipelines that transform data at scale, orchestrated jobs via Airflow, using SQL and Python in Snowflake
• Contributing to Python packages in Github and APIs, using current best practices