Staff/Senior Analytics Engineer, Data Science & Analytics (DSA)

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. Our autonomous robots and multi-modal data collection systems are transforming how retailers manage inventory and make data-driven decisions. We are looking for 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; you'll partner closely with Product Management, Engineering, and Data Scientists to ship reliable, user-facing features that surface insights from our retail data at scale. Establish organized data marts to empower self-serve analytics and AI powered insights. Leveling (Senior or Staff) will be determined through the interview process based on your background and technical depth.

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 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; Establish organized data marts to empower self-serve analytics and AI powered insights; Build conversational data experiences (nice to have)

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; Must currently reside locally; this is not a remote-eligible role

Nice to have

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; Design and prototype AI agent or chatbot interfaces that allow users to query and explore retail data through natural language

Benefits

Ownership that matters: real scope over systems and features that run in production; High-signal environment: focused team where work is visible and technical judgment is trusted; Retail at scale: data spans thousands of stores and billions of shelf observations