Senior Data Platform Engineer

United States·BostonFull Timesenior

Data EngineerData

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Overview

At WHOOP, we are on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives.

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At WHOOP, we are on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives.

We are seeking a Senior Data Platform Engineer to build and evolve the foundational infrastructure that powers our data platform, lakehouse, and real-time data systems. In this role, you will partner closely with data engineers, ML platform engineers, software engineers, and data scientists to design, develop, and operate the core services and workflows that enable reliable, scalable, and efficient data movement across the organization.

As a senior individual contributor, you will own critical parts of the platform end to end - from architecture and implementation to reliability, observability, and operational excellence. You will help shape the technical direction of WHOOP’s data ecosystem, improve developer experience for internal data consumers, and ensure our systems can support analytics, machine learning, and product innovation at scale.This role requires a strong ownership mindset, the ability to operate with minimal guidance, and a focus on delivering production grade systems.

You are also expected to actively leverage AI assisted development tools to improve speed, quality, and maintainability, and to help set the standard for effective AI usage across the team.

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.