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Senior Data Engineer, Data Quality & Experimentation San Francisco, CA - San Francisco California
Company: Strava Location: San Francisco, California
Posted On: 05/01/2025
Senior Data Engineer, Data Quality & ExperimentationAbout This RoleStrava is the app for active people. With over 150 million athletes in more than 190 countries, it's more than tracking workouts-it's where connection, motivation, and personal bests thrive. No matter your activity, gear, or goals, Strava's got you covered. Find your crew, crush your milestones, and keep moving forward. Start your journey with Strava today.We are seeking data engineers to join our Data Team. Our vision is that key decisions and product at Strava can be greatly enriched with data to benefit athletes and the business. Our mission is to build the infrastructure and systems that enable best-in-class data science, analytics, and self-service business intelligence.This means we listen to all corners of the company for opportunities where data can make a difference. We distill this down and use modern technologies to develop both generalized and special purpose data solutions.We follow a flexible hybrid model that generally translates to around half your time on-site in our San Francisco -roughly three days per week.You're excited about this opportunity because you will: - Design, build, and maintain robust, scalable, and efficient ETL/ELT pipelines for Strava's core business data models and analytical data sets.
- Implement monitoring and alerting for the quality and availability of data sets and workflows that guarantee the integrity of Strava's data assets.
- Collaborate with the data team to develop optimizations and best practices and for data science workflows and self-service reporting infrastructure.
- Contribute to Strava's data culture by developing data and tools for self-service exploration, reporting, and experimentation.You will be successful here by:
- Understanding the business relevance of our data sets and ensuring data consumers work from a reliable and accurate foundation.
- Improving the extensibility and efficiency of our data models and self-service tools to create data processes that will scale with our growing user base.
- Proactively identifying the processes and tools will drive the most impact to our data ecosystem.
- Understanding how critical it is we maintain a high bar of data security and privacy.We're excited about you because:
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