Senior Analytics Engineer: Production Data Pipelines & AI

Simbe Robotics; San Francisco (CA); Hybrid; USD 130,000 - 165,000; Full time

Job summary

Simbe Robotics in the San Francisco Bay Area (Hybrid — Burlingame office 2-3x/week required) must currently reside locally; this is not a remote-eligible role. We seek an Analytics Engineer to join our Data Science & Analytics team, owning production-grade data pipelines from ideation through delivery.

You will collaborate with Product Management, Engineering, and Data Scientists to surface insights from retail data at scale, establish organized data marts for self-serve analytics, and apply

Qualifications

• 5+ years of analytics engineering delivering production features.
• dbt for data transformation and Kimball modeling in production workflows.
• Strong SQL and experience with cloud data platforms (BigQuery).
• Experience working across Engineering, Product, or Commercial teams and communicating tradeoffs.

Responsibilities

• Own production analytics pipelines end-to-end with monitoring and alerts.
• Shape raw data into analytical models using Kimball dimensional modeling and dbt.
• Drive cross-functional delivery across teams with minimal blockers.
• Apply AI tooling to accelerate analysis and development.
• Translate store-level signals into meaningful business outcomes for internal teams and clients.
• Raise analytical standards for reproducibility, documentation, and code quality.
• Build conversational data experiences with AI agents or chatbots (nice to have).

Skills

Analytics engineering

dbt

Kimball modeling

SQL

BigQuery

Cross-functional collaboration

Retail data experience

AI tooling experience

Tools

dbt

Looker

Tableau

Airflow

Job description

Simbe Robotics in the San Francisco Bay Area (Hybrid — Burlingame office 2-3x/week required) must currently reside locally; this is not a remote-eligible role. We seek an Analytics Engineer to join our Data Science & Analytics team, owning production-grade data pipelines from ideation through delivery.

You will collaborate with Product Management, Engineering, and Data Scientists to surface insights from retail data at scale, establish organized data marts for self-serve analytics, and apply