Senior Server Engineer (Data Products)

Strava, a well-loved consumer product at the intersection of geo and fitness. As a Senior Data Engineer, you'll build and operate the pipelines and access layer that turn raw data, algorithms, and models into production-ready data products. You'll work closely with ML engineers, data scientists, and product teams to ensure strong reliability, freshness, and clear contracts.

About Strava

Construire et exploiter les pipelines et la couche d'accès qui transforment les données brutes, les algorithmes et les modèles en produits de données prêts pour la production.

Responsibilities

• Collaborer avec les ingénieurs ML, les scientifiques des données et les équipes produit pour expédier des produits de données avec une forte fiabilité, fraîcheur et contrats clairs.
• Contribuer aux outils en libre-service qui facilitent l'utilisation de ces produits par d'autres équipes.

Requirements

• Comfort taking technical ownership within a project or team: making design trade-offs, coordinating with collaborators, and mentoring junior engineers and peers
• Strong communication and collaboration skills with the ability to work effectively with cross-functional partners
• Experience building and operating complex, data-intensive backend systems in production at scale, with a track record of breaking large technical problems into well-scoped, executable work
• Proficiency in backend service development on cloud environments (AWS preferred), using Python, Scala, Go, or equivalent. Solid understanding of distributed systems and containerized infrastructure (Kubernetes, Docker)
• Demonstrated experience building access layers, platform tooling, or internal developer products ideally for large scale data or ML systems with a strong instinct for contract design, versioning, and self-serve patterns

Preferred

• Experience building and maintaining production data pipelines and batch/stream workflows using technologies like Spark, Kafka, Flink, Iceberg, Snowflake, or similar
• Eagerness to engage with ML concepts such embeddings, classification outputs, model evaluation, GenAI integrations. Bonus points if you are already an ML practitioner

Pay

USD 180,375 - 200,850

Benefits

• Enjoy a range of benefits including 100% company-paid benefits for employees and families, flexible paid time off, and a $2,000 annual professional development stipend.

Join

This is a hybrid role with more than half your time spent on-site in our San Francisco office.