Senior Manager, Data Engineering

Strava•San Francisco, CA

38d•$255,000 - $271,000•Hybrid

About The Position

Strava is the app for active people. With over 150 million athletes in more than 185 countries, Strava is where connection, motivation, and personal bests thrive. No matter your activity, gear, or goals, we help you find your crew, crush your milestones, and keep moving forward. Start your journey with Strava today. Our mission is simple: to motivate people to live their best active lives. We believe in the power of movement to connect and drive people forward. We are seeking a strategic and hands-on Senior Manager, Data Engineering to lead a team focused on building and optimizing data pipelines and data models that enable best-in-class data science, analytics, and self-service business intelligence. You will be instrumental in realizing our vision that key decisions and products at Strava are greatly enriched with data to benefit athletes and the business. This role requires a balance of people leadership, technical oversight, and individual contribution to set the strategic direction for our core data assets. You will partner tightly with Analytics, Data Science, and Data Platform teams across the company. We follow a flexible hybrid model that translates to more than half your time on-site in our San Francisco office - three days per week.

Requirements

You have 7+ years of experience in data engineering, data platform, or a related quantitative domain.
You have 3+ years of experience leading and mentoring high-performing data engineering teams.
You are an advanced user of SQL and have developed production-grade data pipelines using languages like Python, Scala, or Java.
You have deep experience implementing and maintaining modern ETL/ELT orchestration systems (e.g., Airflow, dbt) and cloud data infrastructure (e.g., Snowflake, BigQuery, AWS, GCP).
You have a strong track record of driving data quality, governance, and the implementation of tools for data cataloging and monitoring.
You understand underlying infrastructure and engineering best practices (e.g., Kubernetes, CI/CD, software development lifecycle) with the ability to influence architectural decisions.

Responsibilities

Act as the player-coach for our Data Engineering function, fostering a culture of technical excellence and ownership.
Define the long-term vision and technical roadmap for Strava's core data platform, including the development of scalable, robust, and efficient ETL/ELT pipelines.
Drive initiatives to significantly improve the quality, integrity, and availability of Strava's data assets, implementing best-in-class monitoring and alerting systems.
Collaborate with Analytics, Data Science, and Product teams to enable advanced data consumption, experimentation, and self-service business intelligence across the company.
Represent the Data Engineering team in cross-functional strategic planning and collaborate with the broader data community to elevate our technological craftsmanship and data governance standards.
Translating the company's business objectives into a compelling technical strategy for the Data Engineering team, ensuring all data infrastructure supports business relevance.
Prioritizing and driving execution of projects that significantly improve the scalability, efficiency, and extensibility of our data models and systems.
Serving as a key technical and organizational mentor for your team, guiding them on complex architectural decisions and best practices for modern data development.
Proactively anticipating the data needs of a rapidly growing platform, fostering a culture that prioritizes data integrity, security, and privacy.

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