Whoop

Senior Data Platform Engineer

$150K–$215KFull-time · Boston, MA
✓ Verified live on the employer's own system · added 94 days ago
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Mid-level · 5+ yrs exp

Requirements

Experience: 5+ years

Skills & tools

OperationsData AnalysisPythonSQLJavaSales
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Full job description

  • Design, build, and operate the core infrastructure and services that power WHOOP’s data platform, including lakehouse, warehouse, and streaming systems.
  • Improve the performance, reliability, and cost efficiency of our data systems, including Iceberg, Snowflake, and AWS-based data infrastructure.
  • Build and enhance internal tooling, APIs, and automation that improve platform usability and developer experience for data engineers, analysts, and data scientists.
  • Lead platform engineering best practices across CI/CD, infrastructure as code, testing, deployments, and operational readiness.
  • Strengthen observability and operational excellence through monitoring, alerting, incident response, and continuous improvement of production systems.
  • Partner cross-functionally with Data Science, Analytics, ML Platform, and Software Engineering teams to support scalable and efficient data workflows.
  • Drive best practices for data architecture, pipeline design, governance, and platform usage across the company.
  • Leverage AI tools to accelerate development, improve code quality, and enhance debugging and documentation workflows
  • 5+ years of experience in data engineering, platform engineering, or software engineering with significant ownership of production data systems.
  • Strong proficiency in Python and SQL. Java experience is nice to have.
  • Experience designing and operating scalable data platforms, pipelines, or distributed data systems in production environments.
  • Hands-on experience with Snowflake and modern cloud data infrastructure.
  • Experience with AWS services such as S3, EKS, EMR, EC2, or related cloud-native infrastructure.
  • Experience with orchestration frameworks such as Airflow or Prefect.
  • Strong understanding of CI/CD, infrastructure as code, and DevOps practices for data platforms.
  • Ability to independently drive technical projects and own systems end to end with a high degree of autonomy.
  • Strong communication and collaboration skills, with the ability to work effectively across engineering and data teams.
  • Commitment to leveraging AI-assisted development tools thoughtfully and effectively, while maintaining a high bar for engineering quality.

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