Tech Stack

Description

You will design and build scalable data systems and AI/ML workflows, contributing to a modern data stack in a behavioral health setting. Partnering with data scientists and product managers, you'll create reliable infrastructure that enables faster, data-driven decisions while mentoring peers.

Requirements

• Bachelor's degree in Computer Science, Data Science, or related field
• 5+ years experience in data engineering, platform engineering, or ML engineering
• Experience with AWS/GCP, dbt, Airflow, Airbyte, Redshift/BigQuery
• Proficiency in SQL and Python with modern data engineering frameworks
• Knowledge of ML frameworks (e.g., Spark, TensorFlow, PyTorch) and ability to build production APIs

Responsibilities

• Design and maintain scalable data ingestion, transformation, and storage systems with focus on testing and observability
• Implement frameworks, tooling, and automation to increase development velocity
• Develop end-to-end AI/ML workflows including source ingestion, training, experimentation, and production integration
• Support iterative model development and production observability (accuracy, drift, bias, fairness)
• Contribute to a culture of continuous improvement and mentoring peer engineers