Senior Data Engineer - Data Operations

📋 Description

• Build and maintain scalable data ingestion infrastructure and ops systems.
• Focus on the EL portion of the ELT stack; collaborate with analytics engineers.
• Develop robust, config-driven, event-driven pipelines for large datasets.
• Migrate data incrementally from RDS and DynamoDB into Snowflake using Kinesis or Airbyte.
• Create staging-layer architecture supporting medallion design.
• Remote work: private space and fast internet; occasional on-site meetings.

🎯 Requirements

• 4-6+ years in data engineering focusing on ingestion and infrastructure.
• Python and SQL proficiency with production-grade pipelines.
• Ingestion tools such as Kinesis, Airbyte, Kafka or similar.
• Hands-on Snowflake experience and moving data from ops DBs to cloud warehouse.
• AWS services knowledge including S3, Lambda, Step Functions and RDS.
• Docker and Kubernetes experience for maintainable deployments.

🎁 Benefits

• Dynamic role in a growing startup.
• Opportunity to shape healthcare data products.
• Strong learning and growth opportunities.
• Collaborative cross-functional teams.
• Remote-friendly with occasional on-site meetings.