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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and operating complex data-intensive backend systems, with a strong focus on data product delivery, pipeline design, and operational health best practices. Proficient in backend service development within cloud environments and experienced in mentoring engineering teams.
Highest-signal resume keywords
Data Pipeline DevelopmentBackend Service DevelopmentCloud Environments (AWS)Distributed SystemsMentoring Experience
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonScalaGoSparkKafkaFlinkIcebergSnowflakeContract DesignVersioning
Soft Skills
Strong CommunicationCollaboration Skills
Tools & Technologies
KubernetesDocker
Industry Keywords
Data-Intensive SystemsML SystemsSelf-Serve PatternsOperational Health Best PracticesGeo Datasets
Tech Stack
Tools & technologiesAWSCloudDistributed SystemsDockerKafkaKubernetesPythonScalaSparkGo
About the role
Key responsibilities & impact- Build and operate pipelines, APIs, and platform tooling exposing Strava’s derived data products as reliable, well-documented internal products
- Build self-serve interfaces and golden paths enabling product and CUJ engineering teams to use core data products
- Own data product delivery end-to-end, from pipeline design and artifact schema through production deployment and monitoring
- Ensure data product correctness, freshness, reliability, versioning, contracts, SLAs, monitoring, and deprecation paths
- Collaborate with ML engineers, data engineers, data scientists, product managers, and Data Platform
- Integrate model outputs into durable, versioned artifacts
- Contribute to compute patterns and cost efficiency
- Explore Strava’s fitness and geo datasets to extract actionable insights and inform product decisions
- Establish data product development and operational health best practices
- Mentor junior and mid-level engineers
Requirements
What you’ll need- Experience building and operating complex, data-intensive backend systems in production at scale
- Demonstrated experience building access layers, platform tooling, or internal developer products for large-scale data or ML systems
- Experience with contract design, versioning, and self-serve patterns
- Experience building and maintaining production data pipelines and batch/stream workflows using Spark, Kafka, Flink, Iceberg, Snowflake, or similar
- Proficiency in backend service development in cloud environments, AWS preferred
- Proficiency in Python, Scala, Go, or equivalent
- Solid understanding of distributed systems and containerized infrastructure, including Kubernetes and Docker
- Technical ownership, design trade-offs, collaborator coordination, and mentoring experience
- Eagerness to engage with ML concepts such as embeddings, classification outputs, model evaluation, and GenAI integrations
- Strong communication and collaboration skills
- Ability to work onsite in the San Francisco office three days per week
Benefits
Comp & perks- Equity
- Inclusive and collaborative workplace culture
- Reasonable accommodation for individuals with disabilities
- Benefits and privileges of employment (details linked in posting)