Senior Data Engineer

Whoop•Boston, MA

1d•$150,000 - $215,000

About The Position

At WHOOP, we're 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. WHOOP is hiring a Senior Data Engineer to lead the design, development, and evolution of the data systems that power analytics, experimentation, machine learning, and business decision-making across the company. In this role, you will own complex data engineering initiatives from design through production, partnering closely with Data Science, Analytics, Product, and Engineering teams to build reliable, scalable, and well-governed data solutions. As a senior member of the team, you'll raise the technical bar through mentorship, thoughtful engineering practices, and a commitment to continuously improving how Data Engineering operates.

Requirements

Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
5+ years of professional experience designing, building, and operating production data engineering systems.
Strong proficiency with Python, SQL, and modern ELT development practices, with experience building maintainable, testable, and observable data pipelines.
Experience designing and optimizing data warehouse solutions in Snowflake or comparable cloud data platforms.
Experience building and maintaining data transformation frameworks using dbt or similar tooling.
Experience working with distributed data processing technologies such as Spark, Kafka, or equivalent modern data processing frameworks.
Demonstrated ability to independently lead complex technical initiatives involving multiple stakeholders from planning through production support.
Experience mentoring engineers, providing thoughtful technical feedback, and helping raise engineering quality across a team.
Strong communication skills with the ability to explain technical concepts, navigate tradeoffs, and build alignment across engineering and business stakeholders.
Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions.

Responsibilities

Lead the design, implementation, and long-term ownership of scalable ELT pipelines and data workflows using Python, PySpark, SQL, and modern cloud technologies.
Design and optimize data models and Snowflake architectures that enable reliable, performant, and trusted data consumption across analytics, experimentation, and machine learning use cases.
Own complex cross-functional data initiatives, translating ambiguous business requirements into maintainable technical solutions while proactively identifying risks, dependencies, and tradeoffs.
Partner closely with Product, Engineering, Analytics, Data Science, and the Data Platform Engineering team to ensure data systems are reliable, scalable, and aligned with evolving business needs.
Drive improvements in data quality, observability, testing, documentation, and operational excellence, establishing patterns and best practices that improve the effectiveness of the broader team.
Mentor Data Engineers through design discussions, code reviews, and technical coaching while contributing meaningfully to hiring, onboarding, and interview processes.
Contribute to the technical direction of the Data Engineering organization by evaluating new technologies, improving engineering standards, and identifying opportunities to simplify, automate, and scale our data ecosystem.
Leverage AI tools and automation to accelerate development, improve engineering quality, and increase team productivity while maintaining rigorous validation, security, and engineering standards.