Sr. Data Engineer

About this role

About the Company:

Octave is a modern behavioral health practice creating a new standard for care delivery that’s both high-quality and accessible. With in-person and virtual clinics in multiple states, the company offers evidence-based individual, couples, and family therapy, while pioneering relationships with payers to make care more affordable through insurance. By raising the bar on how care is delivered and how providers are supported, we are building a sustainable system that values equity, affordability, and effectiveness.

Job Summary:

We’re looking for a Sr. Data Engineer with strong data platform experience to help evolve our modern data stack and contribute to the foundation of our emerging AI and ML platform. This role sits at the intersection of data engineering, platform architecture and machine learning enablement and will bring high-quality, scalable, and ethical AI into real-world use. You will partner closely with data scientists, analysts, and product managers to ensure our platform supports reliable data pipelines, scalable analytics, in addition to defining new architecture, best practices, and patterns for fellow engineers to inherit. The ideal candidate is both a systems thinker and a hands-on builder who thrives in evolving environments and is passionate about creating reliable data infrastructure that enables peers and partner teams to move faster with data. You will have the opportunity to learn and contribute to a machine learning enablement and will bring high-quality, scalable, and ethical AI into real-world use.

Duties & Responsibilities:

• Design, build, and maintain scalable systems for ingestion, transformation, and storage of data, with a focus on testing and observability.

• Implement frameworks, tooling, and automation to safely increase development velocity.

• Develop foundational end-to-end AI/ML workflows from (1) source ingestion and preparation, (2) training and tuning, (3) experimentation and productionisation, and (4) downstream systems integration (EHR modules, micro-services, dashboards).

• Support iterative model development and production operations and observability (accuracy, drift, bias, fairness, reproducibility).

• Contribute to a culture of continuous improvement, knowledge-sharing and mentoring of peer engineers.

• Leverage AI tools as a core part of daily work (drafting, research, iteration) to improve efficiency, quality, and decision-making.

Required Skills:

• Proficiency in SQL and Python with strong familiarity towards modern data engineering frameworks, infrastructure, and tooling.

• Proficiency with data ops best practices, monitoring, pipeline automation, and CI/CD.

• Knowledge of modern compute and ML frameworks/libraries (i.e., Spark, TensorFlow, PyTorch, scikit-learn).

• Ability to build production APIs and services, inclusive of MCP servers that expose internal data/services to LLMs.

• A collaborative mindset, dependable execution, drive to reflect and improve, and humility to ask questions and learn.

• Comfort using AI tools in day-to-day workflows, with a willingness to continuously rethink and improve how work gets done.

• Curiosity and openness to experimenting with new tools and approaches; prior experience with AI tools is a plus.

• Nice to have:

• Experience with foundational end-to-end AI/ML workflows from (1) source ingestion and preparation, (2) training and tuning, (3) experimentation and productionization, and (4) downstream systems integration (EHR modules, micro-services, dashboards).

• Some knowledge of modern compute and ML frameworks/libraries (i.e., Spark, TensorFlow, PyTorch, scikit-learn).

• Some experience with building production APIs and services, inclusive of MCP servers that expose internal data/services to LLMs.

Education & Experience:

• Bachelor’s degree (or equivalent) in Computer Science, Data Science, Statistics, Engineering or a related field.

• 5+ years of experience in data engineering, platform engineering, or ML engineering.

• Experience working with major cloud data platforms and tools:

• Preferred experience:

• Healthcare, behavioral health, EHR systems, and/or regulated industries.

• Specific expertise with: AWS/GCP, dbt, AirflowAirbyte, Redshift/BigQuery.

Octave's Company Values:

The below values drive our day-to-day operations.

• We’re human beings first. We operate with empathy and kindness – with our clients, with our collaborators, and with ourselves.

• People deserve better than status quo. We’re willing to tackle the intractable problems, no matter how big, because someone should. We ask big questions, we craft big solutions, and we challenge ourselves and others to make it happen.

• No bystanders. No stars. No tourists. Each person has been selected to be here, and with that comes a responsibility to bring your expertise, share your ideas, and help make this company better.

• Partnership paves the path ahead. We don’t operate in a silo, internally or externally. To transform the system, we believe in working with others to create something bigger, better, and stronger.

• Quality is crucial at scale. Quality is core to our business, and we refuse to sacrifice it as we grow.

• Progress is a process. In the pursuit of progress, we iterate, reflect, learn, adjust – and always leave things better than we found them.

• There are people behind every data point. We recognize that numbers tell only one part of the story, and we also do the work to understand impacts at the individual level.

Physical Requirements:

• Prolonged periods sitting at a desk and working on a computer.

• Must be able to frequently communicate with others through virtual meeting applications such as Zoom and Google Meet.

• Must be able to observe and communicate information on company provided laptop.

• Move up to 10 pounds on occasion.

• Must be eligible to work in the United States without sponsorship now or in the future.

Compensation, Equity & Incentives:

Base Sal

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