Senior Data Engineer Build Scalable Governed Pipelines

User Interviews; San Francisco (CA); Hybrid; USD 140,000 - 210,000; Full time

Job summary

Strava is seeking a Senior Data Engineer to join our Data Team to design and operate data pipelines, models, and governance across our data warehouse and data lake. You will build scalable ingestion and transformation frameworks with dbt, Airflow, and Spark, and collaborate with analytics engineers, data scientists, and security teams.

This role follows a flexible hybrid model with three days on-site in San Francisco, supporting analytics, data governance, and privacy initiatives.

Qualifications

• 3–5+ years of professional experience in Data Engineering, Data Infrastructure, Software Engineering, or a related field.
• Strong expertise in SQL and data modeling for large-scale analytics.
• Experience building and operating ETL/ELT and data processing systems with dbt, Airflow, Spark.
• Proficient in at least one language such as Python, Scala, Java, or Go.
• Understanding of modern data warehouse and data lake architectures (Snowflake, Databricks, BigQuery, Redshift, Iceberg, Delta Lake).

Responsibilities

• Design, build, and operate foundational data systems and data assets for analytical and business use cases.
• Build scalable data ingestion and transformation frameworks across data lake and data warehouse.
• Develop reusable data engineering tools and abstractions (dbt-centric workflows).
• Create durable domain data models (e.g., user, subscription, activity) with clear semantics and lineage.
• Build governance, privacy, and GDPR workflows across data platforms.
• Improve reliability via testing, data quality checks, lineage, monitoring, and observability.

Skills

SQL and data modeling

Cloud data platforms (AWS/GCP/Azure)

Programming languages (Python/Scala/Go

Data architecture & domain modeling

Data governance & GDPR awareness

Tools

dbt

Airflow

Spark

Kubernetes

Iceberg/Delta Lake

Data catalogs & lineage

Job description

Strava is seeking a Senior Data Engineer to join our Data Team to design and operate data pipelines, models, and governance across our data warehouse and data lake. You will build scalable ingestion and transformation frameworks with dbt, Airflow, and Spark, and collaborate with analytics engineers, data scientists, and security teams.

This role follows a flexible hybrid model with three days on-site in San Francisco, supporting analytics, data governance, and privacy initiatives.