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Salary: USD 182,000 - 228,000 / annual
Turo, the world's largest car sharing marketplace, is seeking a Staff Data Engineer to build and operate a modern, scalable data platform that powers analytics and pipelines across the organization.
In this role, you will collaborate with cross-functional teams to design and implement resilient systems for collecting and analyzing large-scale datasets. You will own the data platform architecture that enables Product, Engineering, Data Science, Marketing, Customer Operations, and Finance teams to design, operate, and maintain data pipelines and reports. Key responsibilities include:
- Collaborating daily with team members to refine the data engineering roadmap and drive execution of strategic initiatives
- Designing and implementing a modern, highly scalable and reliable data platform powering pipelines across multiple business functions
- Defining canonical data models across key business domains and establishing a cohesive vision for unifying all data within the Turo ecosystem
- Implementing, operating, and supporting workflow orchestration tooling such as Airflow in cloud-based environments
- Building, operating, and continually improving data platform tools and infrastructure to boost team productivity and minimize operational overhead
- Mentoring and developing junior engineers to increase overall team effectiveness
- Designing and enforcing robust data security architectures and controls
This is a hybrid role requiring in-office presence 3 days per week (Mondays, Wednesdays, Thursdays) in San Francisco.
REQUIREMENTS:
- 7+ years of relevant experience in data engineering or related field
- Solid foundation in software engineering with proven track record of developing well-tested, reusable code frameworks and libraries
- Past experience building ETL frameworks
- Experience with data pipeline job orchestration tools such as Airflow, Prefect, or Dagster
- Experience using data platforms and services across major cloud providers (AWS, GCP, Azure)
- Proficiency with modern infrastructure tooling, including Terraform and Kubernetes
- Knowledge of security standards and frameworks that govern robust data protection
- Ability to understand technical details and communicate with engineers and less technical stakeholders
- Mentoring and teaching capability
- Clear understanding of AI capabilities and constraints, with ability to integrate AI into daily workflows
- Familiarity with Spark or other big data processing frameworks (preferred)
