Eight Sleep
Clinical Data Engineer
Boston Area · Mid · Full-time
Sponsorship not specified$110k-$130kDetected 77 days ago
PythonAlgorithmsSQLSnowflakeAWSGCPMachine LearningPandasNumPyData AnalysisData EngineeringData ScienceStatisticsSignal ProcessingAvidClinical TrialsClinical ResearchFDA RegulatoryResearchCommunicationCollaborationPublic Speaking
About the role
- Ensure data integrity, reproducibility, and proper versioning across evolving datasets and analyses
- Leverage AI-assisted tools to accelerate data analysis, debugging, and code development, improving iteration speed and reducing manual effort
- Investigate edge cases, sensor issues, and data anomalies to improve model robustness
Responsibilities
- We're here to build fast, push limits, and deliver without compromise.
- Build and maintain scalable ETL pipelines using Python, SQL, and APIs to ingest and process large-scale biometric and sensor data
- Manage data storage, retrieval, and archival systems in AWS, including handling long-term access and data restore workflows
- We are a small team that empowers you to own your projects and see the tangible effects of your efforts, enhancing both your professional growth and our company's trajectory.
- Every Eight Sleep employee receives the very product that defines our mission: a Pod of their own.
- If you join us you'll get your own Pod, along with*:
Requirements
- Advanced Python and SQL proficiency - Pandas, NumPy, time-series analysis, and production-quality scripting are daily tools, not occasional ones
- Working proficiency with AWS and Snowflake - you've built or maintained cloud-based data storage, retrieval, and archival systems, not just queried them
- Experience with clinical or regulatory trial data, familiarity with GCP/ICH guidelines, or prior work supporting FDA submissions
- Experience integrating internal and third-party APIs into unified data pipelines
- Strong cross-functional communication skills. ability to translate complex analyses into clear insights for non-technical stakeholders
Compensation
- Compensation is based on experience, qualifications, and market benchmarks for the Boston metro area.
- Equity and performance-based incentives are a significant component of total compensation at Eight Sleep.
- $110,000 - $130,000
- Equitable Compensation and Continuous Equity Investment
Benefits
- 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.
- We are trusted by high performers, professional athletes, and health-conscious consumers in over 30 countries worldwide.
- Equitable Compensation and Continuous Equity Investment
- We extend equity participation to every full-time team member, recognizing and rewarding your direct contributions to our success.
- This includes periodic equity refreshments based on performance, ensuring that as Eight Sleep grows and succeeds, so do you - perfectly aligning your achievements with the broader triumphs of the company.
- Your Own Pod - and Other Great Benefits
- 2+ years of data engineering experience with health/physiology data in a research context - you've built ETL pipelines around messy, real-world biometric or sensor datasets, not just clean CSVs
Company info
- Full access to health, vision, and dental insurance for you and your dependents
- Supplemental life insurance
- Flexible PTO
- Commuter benefits to ease your daily commute
- Paid parental leave
- We operate with intensity because our mission demands it.
- At Eight Sleep, we're on a mission to fuel human potential through optimal sleep.
Equal opportunity
- As an equal opportunity employer, we stay true to our values by ensuring everyone feels they can flourish and grow.
Visa & Work Authorization
- al employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status
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This listing is sourced directly from Eight Sleep's careers page and normalized into a canonical job model.