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Octave is a modern behavioral health practice delivering high-quality, accessible care through in-person and virtual clinics across multiple states. The company offers evidence-based individual, couples, and family therapy while pioneering relationships with payers to make care more affordable through insurance.
We are seeking a Senior Data Engineer to evolve our modern data stack and build the foundation of our emerging AI and ML platform. This role sits at the intersection of data engineering, platform architecture, and machine learning enablement, bringing high-quality, scalable, and ethical AI into real-world healthcare use.
Key Responsibilities:
- Design, build, and maintain scalable systems for data ingestion, transformation, and storage with emphasis on testing and observability
- Implement frameworks, tooling, and automation to safely increase development velocity
- Develop foundational end-to-end AI/ML workflows covering source ingestion and preparation, training and tuning, experimentation and productionization, and downstream systems integration (EHR modules, microservices, dashboards)
- Support iterative model development and production operations, monitoring accuracy, drift, bias, fairness, and reproducibility
- Contribute to continuous improvement, knowledge-sharing, and mentoring of peer engineers
- Leverage AI tools as a core part of daily work to improve efficiency, quality, and decision-making
Required Qualifications:
- Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or related field
- 5+ years of experience in data engineering, platform engineering, or ML engineering
- Proficiency in SQL and Python with strong familiarity with modern data engineering frameworks, infrastructure, and tooling
- Proficiency with data ops best practices, monitoring, pipeline automation, and CI/CD
- Experience with GCP or AWS data engineering tools and big data frameworks
- Experience with data modeling and medallion architecture
- Collaborative mindset with dependable execution and drive for continuous improvement
- Comfort using AI tools in day-to-day workflows
Preferred Experience:
- Healthcare, behavioral health, EHR systems, or regulated industry experience
- Expertise with AWS/GCP, dbt, Airflow, Airbyte, Redshift, or BigQuery
- End-to-end AI/ML workflow development
- Modern compute and ML frameworks (Spark, TensorFlow, PyTorch, scikit-learn)
- Building production APIs and services, including MCP servers for LLM integration
