Clinical Data Engineer

Join the Sleep Fitness Movement

At Eight Sleep, we’re on a mission to fuel human potential through optimal sleep. As the world’s first sleep fitness company, we’re redefining what it means to be well-rested and building the most advanced hardware, software, and AI technology to make it possible. Our products power peak mental, physical, and emotional performance by transforming every night of sleep into a personalized, data-driven recovery experience. We are trusted by high performers, professional athletes, and health-conscious consumers in over 30 countries worldwide.

Recognized as one of Fast Company’s Most Innovative Companies in 2019, 2022, 2023, 2026, and twice named to TIME’s “Best Inventions of the Year.”

We operate like a high-performance team: fast, focused, and motivated by impact. We don’t just ship; we iterate, refine, and obsess over the details that help our members sleep better and wake up stronger.

High Standards. No Apologies.

We operate with intensity because our mission demands it. At Eight Sleep, we bring the same mindset as the world’s top performers: focused, relentless, and always pushing to be in the top 1% of our craft. Think Kobe Bryant’s mamba mentality, applied to bold ideas, next-gen tech, and flawless execution. This isn’t a 9-to-5. Our team is deeply committed, often putting in the extra effort — not because we’re told to, but because we’re invested.

We’re here to build fast, push limits, and deliver without compromise. If you thrive under pressure and want to do the most meaningful work of your career, you’ll feel right at home. If you’re looking for something easier — this isn’t it.

The Role

We’re looking for a Clinical Data Engineer who will own the end-to-end data pipelines for our clinical studies, including regulatory trials. You will create monitoring tools for tracking live data out in the field that can alert the research associates to any issues, work closely with ML/AI to ensure that incoming data are stored in formats that are easily ingestible and clearly labeled, and work to align datasets with multiple incoming sources of data for analysis by our team.

Additionally, you will own the data analysis for our hardware validation studies (heart rate, heart rate variability, and presence), helping to make key go/no-go decisions for the company. You’ll be the connective tissue between our internal teams and the external clinical sites, and can continuously think outside the box to make our studies more efficient for the research associates and data scientists.

You will operate at the intersection of data engineering, applied data science, and clinical research by working directly with raw sensor data from all of our products, along with the ground truth data to validate our algorithms to make key product decisions. You will own the end-to-end data lifecycle, from ingestion to analysis to communication. This role is highly cross-functional with hardware, software, product, and research teams.

How You'll Contribute

Data Engineering & Infrastructure

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Build and maintain scalable ETL pipelines using Python, SQL, and APIs to ingest and process large-scale biometric and sensor data

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Design data models and workflows that support clinical studies, internal tools, and downstream analytics

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Manage data storage, retrieval, and archival systems in AWS, including handling long-term access and data restore workflows

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Ensure data integrity, reproducibility, and proper versioning across evolving datasets and analyses

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Leverage AI-assisted tools to accelerate data analysis, debugging, and code development, improving iteration speed and reducing manual effort

Clinical Analytics & Algorithm Validation

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Analyze sleep, physiological, and behavioral datasets to evaluate product performance and validate new features

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Perform statistical analyses (e.g., correlation, error metrics, bootstrapping, validation frameworks) to assess algorithm accuracy and clinical outcomes

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Develop evaluation pipelines for metrics like HR/HRV accuracy, presence detection, and sleep staging

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Build tools and structured datasets to support training and validation of machine learning models, integrating multiple data sources for supervised learning

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Investigate edge cases, sensor issues, and data anomalies to improve model robustness

Internal Tooling & Visualization

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Maintain and extend Python-based applications for visualizing and annotating biometric data

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Develop interactive tools for researchers and engineers to inspect sessions, validate signals, and debug algorithms

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Streamline workflows for clinical teams to reduce manual effort and improve reproducibility

Cross-Functional Collaboration & Communication

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Partner with Machine Learning, Hardware, Firmware, and Product teams to build algorithms and test prototypes

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Work with Growth and Product teams to explore user behavior and inform feature development

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Synthesize findings into reports, dashboards, and presentatio