Senior Analytics Engineer: Production Data Pipelines & AI

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

Job summary

Simbe Robotics in the San Francisco Bay Area is seeking an Analytics Engineer to own production-grade data pipelines from ideation through delivery. This engineering-forward role partners with Product Management, Engineering, and Data Scientists to surface insights from our retail data at scale.

You will establish organized data marts for self-serve analytics, apply AI tooling to accelerate work, and translate store-level signals into meaningful business outcomes for internal teams and retail

Qualifications

• 5+ years of analytics engineering experience with production features
• dbt for data transformation and Kimball dimensional modeling
• Strong SQL and experience with large-scale cloud data platforms (GCP/BigQuery)
• Experience owning the full lifecycle of analytics features
• Ability to work across Engineering, Product, or Commercial teams
• Retail industry experience strongly preferred
• Hands-on experience using AI tools for analytics

Responsibilities

• Own production pipelines end-to-end — design, build, and maintain analytics pipelines with monitoring and updates
• Scope and deliver features — shape raw data into analytical models via Kimball dimensional modeling
• Drive cross-functional delivery — unblock blockers and align stakeholders across teams
• Apply AI tooling to accelerate work — leverage LLMs, agents, and AI workflows
• Translate retail data into decisions — connect store signals to business outcomes
• Raise analytical standards — promote reproducibility, documentation and code quality
• Build conversational data experiences — prototype AI agents for querying data

Tools

dbt

Kimball dimensional modeling

BigQuery

Looker

Tableau

Airflow

LLM APIs

Job description

Simbe Robotics in the San Francisco Bay Area is seeking an Analytics Engineer to own production-grade data pipelines from ideation through delivery. This engineering-forward role partners with Product Management, Engineering, and Data Scientists to surface insights from our retail data at scale.

You will establish organized data marts for self-serve analytics, apply AI tooling to accelerate work, and translate store-level signals into meaningful business outcomes for internal teams and retail