Data Engineer
Tarro· Data Products
Hybrid (San Mateo, CA)$180k - $350kFull-timePosted 8mo ago
About the role
Data Engineer to build and scale Tarro’s data infrastructure, shaping how data is collected, modeled, validated, and consumed across the company.
Responsibilities
- You will build and evolve Tarro’s core data infrastructure and foundational datasets
- You will design, develop, and maintain scalable data pipelines that support analytics, machine learning, experimentation, and product use cases
- You will ensure data quality and reliability by implementing audits, alerting, and anomaly detection at scale
- You will partner closely with Product Managers, Engineers, and business stakeholders to understand data needs and deliver trusted, actionable data
- You will contribute to shared data engineering tooling, standards, and best practices to improve team productivity and output quality
- You will help establish long-term data architecture that scales with Tarro’s growth
Qualifications
- 5+ years of experience building and operating production-grade data pipelines
- Strong understanding of scalable, performant data modeling patterns across structured and unstructured data sources
- Proven ability to work cross-functionally to design data architectures that support analytics, machine learning, and experimentation
- Experience building and operating fault-tolerant, distributed systems
- Hands-on experience working in a cloud environment such as AWS or GCP
- Self-starter who thrives in an environment with high ownership, limited process, and lots of autonomy
- Care deeply about building reliable systems that solve real customer and business problems
Skills
Required:Data pipeline developmentData modelingDistributed systemsCloud platformsCross-functional collaborationReliability and quality
Last updated Jul 16, 2026. Interested? Apply on the company site.
About Tarro
Powering Restaurants to Make More Money – Tarro
Discover how Tarro helps restaurants boost profits with restaurant technology powered by AI. Learn more here.
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