Solutions Engineer

Responsibilities

• Execute and monitor large-scale data transfers across AWS S3, Google Cloud Storage, Azure Blob, Snowflake, and customer environments
• Use Python and SQL to join datasets, clean data, and validate CSV, Parquet, and database tables
• Manage credentials, permissions, manifests, and delivery packaging artifacts for ingestion and handoff workflows
• Leverage Dagster-based platforms to orchestrate data processing and delivery
• Build lightweight scripts and command-line workflows for filtering, manifest generation, and recovery
• Document steps, outputs, and recovery paths to ensure auditability and repeatability
• Partner with Engineering to turn manual operational work into repeatable platform capabilities

Requirements

• Strong hands-on experience with production data pipelines
• Proficiency in Python, SQL, and Bash/shell
• Command-line fluency in Linux or MacOS
• Experience with cloud storage systems and large-scale cross-cloud data movement
• High bar for data integrity, validation, and auditability, especially for regulated data
• Calm, methodical debugging instincts and strong operational judgment

Preferred Qualifications

• Experience with AWS S3, GCS, Azure Blob, or Snowflake
• Experience with IAM debugging
• Familiarity with Dagster or Airflow
• Experience working with healthcare data or AI training data

About the Company

Protege is building a platform to solve the biggest unmet need in AI: getting access to the right training data. We facilitate the secure, efficient, and privacy-centric exchange of AI training data. We are a lean, fast-moving, high-trust team of builders obsessed with velocity and impact.