🛠 Tech Stack

💼 About This Role

You'll own cross-cloud data movement and delivery for large-scale healthcare datasets, using tools like rclone and Python to ensure safe, repeatable operations. You'll debug failures and maintain high data integrity for regulated healthcare data. This role combines production engineering with data pipeline reliability in a fast-moving AI startup.

🎯 What You'll Do

• Execute and monitor large-scale data transfers across AWS, GCP, Azure, and Snowflake.
• Use Python and SQL to join, clean, and validate healthcare datasets.
• Operate Dagster-based pipelines for data processing and delivery.
• Document delivery steps and recovery paths for auditability.

📋 Requirements

• Hands-on experience with data pipelines in production environments.
• Fluency with CLI tools in Linux/MacOS and scripting in Python, SQL, Bash.
• Experience with cloud storage systems and cross-cloud data movement.
• High bar for data integrity and validation for regulated data.

✨ Nice to Have

• Experience with AWS S3, GCS, Azure Blob, Snowflake.
• IAM debugging and cloud permissions management.
• Healthcare data or AI training data experience.

🎁 Benefits & Perks

• 🚀 Real ownership and autonomy in a high-trust environment.
• 💡 Fast-moving culture with bias toward action and learning.
• 🤝 Kind, direct, inclusive team that gives early feedback.
• 🏆 Builders at heart – hands-on and resourceful.

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager Interview· 45 min