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Simbe Robotics is a leading retail robotics company providing in-store intelligence solutions that help retailers optimize operations, improve shelf execution, and deliver valuable data insights. We are seeking an experienced Analytics Engineer to join the Data Science & Analytics team, owning production-grade data pipelines from ideation through delivery.
This is an engineering-forward role where you will partner closely with Product Management, Engineering, and Data Scientists to ship reliable, user-facing features that surface insights from retail data at scale. You will establish organized data marts to empower self-serve analytics and AI-powered insights.
Key Responsibilities:
- Own production pipelines end-to-end: design, build, and maintain robust analytics pipelines that run reliably in production, including monitoring, alerting, and iterative improvement
- Scope and deliver features: take raw data and shape it into analytical models via Kimball Dimensional modeling with dbt
- Drive cross-functional delivery: proactively identify blockers, align stakeholders across teams, and move projects forward with minimal oversight
- Apply AI tooling to accelerate work: leverage LLMs, agents, and other AI-assisted workflows to increase the speed and quality of analysis and development
- Translate retail data into decisions: connect store-level signals (inventory, on-shelf availability, task execution, etc.) to meaningful business outcomes for both internal teams and retail clients
- Raise analytical standards: establish best practices for reproducibility, documentation, and code quality across the team's data science and analytics work
- Build conversational data experiences: design and prototype AI agent or chatbot interfaces that allow internal or external users to query and explore retail data through natural language (nice to have)
You thrive at the intersection of data and software engineering: you write production code, own the reliability of the systems you build, and drive cross-functional projects to completion without waiting to be unblocked. Leveling (Senior or Staff) will be determined through the interview process based on your background and technical depth.
Requirements:
- 5+ years of experience in analytics engineering or a closely related role, with demonstrable delivery of production features
- Experience with dbt for data transformation and Kimball Dimensional modeling: writing models, tests, and documentation as part of a production analytics engineering workflow
- Solid SQL and experience working with large-scale cloud data platforms (GCP/BigQuery preferred)
- Experience owning the full lifecycle of analytics features: scoping, building, shipping, and maintaining
- Proven ability to work across functions: you've partnered with Engineering, Product, or Commercial teams and know how to communicate tradeoffs and drive alignment
- Retail industry experience strongly preferred (store operations, inventory, merchandising, supply chain, or equivalent)
- Hands-on experience using AI tools (LLM APIs, coding assistants, prompt engineering) to accelerate analytical work
Preferred Qualifications:
- Familiarity with pipeline orchestration (Airflow or similar), model monitoring, CI/CD for analytical workflows
- Experience with data visualization tools (Looker, Tableau, or similar) for communicating findings to non-technical stakeholders
