S
New
USD 130000–165000/yr

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

San FranciscoFull-timesenior
Data EngineerData
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Quick Summary

Overview

San Francisco Bay Area (Hybrid — Burlingame office 2-3x/week required) Must currently reside locally; this is not a remote-eligible role.

Technical Tools
Data EngineerData

San Francisco Bay Area (Hybrid — Burlingame office 2-3x/week required)
Must currently reside locally; this is not a remote-eligible role.


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.

You are someone who thrives 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.

  • 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)

  • 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

  • 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

  • Ownership that matters — you'll have real scope over systems and features that run in production and directly affect how our retail partners operate

  • High-signal environment — focused team where your work is visible and your technical judgment is trusted

  • Retail at scale — Simbe's data spans thousands of stores and billions of shelf observations, a genuinely rich and challenging domain

  • At Simbe, you will be at the forefront of retail innovation, working with cutting-edge AI and robotics technologies to transform retail operations. Our culture is dynamic, inclusive, and driven by a passion for improving the way retailers operate and serve their customers. Join us to be a part of a team that is not only reshaping the future of retail but also offering immense value to our clients worldwide.

    Simbe Values: R. E. T. A. I. L.

    Result Driven - We are customer-centric and results-driven. We strive to create immense value for our team, partners, customers, and investors.

    Empathetic - We are sensitive and mindful. We support each other in challenging times, both professionally and personally.

    Transparent - We highly value open communication internally, and with our partners and customers. We are receptive to feedback.

    Agile - We are agile and always eager to learn. We quickly adapt to changes and customer needs.

    Innovative - We are bold and innovative, with an intense focus on product design and user experience.

    Leaders - We strive for excellence. We are accountable, the best at what we do, and leaders in our field.

    Location & Eligibility

    Where is the job
    San Francisco Bay Area
    Hybrid — some on-site time required
    Who can apply
    Open to applicants worldwide

    Listing Details

    Posted
    September 15, 2026
    First seen
    September 15, 2026
    Last seen
    September 18, 2026

    Posting Health

    Days active
    0
    Repost count
    0
    Trust Level
    73%
    Scored at
    September 15, 2026

    Signal breakdown

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    S
    Staff/Senior Analytics Engineer, Data Science & Analytics (DSA)USD 130000–165000