Staff/Senior Analytics Engineer (Data Science & Analytics)
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
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)
BenefitsComprehensive health plans
Culture of learning
Flexible time off
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 unblockedExperience owning the full lifecycle of analytics features: scoping, building, shipping, and maintainingHands-on experience using AI tools (LLM APIs, coding assistants, prompt engineering) to accelerate analytical workExperience with dbt for data transformation and Kimball Dimensional modeling: writing models, tests, and documentation as part of a production analytics engineering workflow 5+ years of experience in analytics engineering or a closely related role, with demonstrable delivery of production featuresSolid SQL and experience working with large-scale cloud data platforms (GCP/BigQuery preferred) Retail industry experience strongly preferred (store operations, inventory, merchandising, supply chain, or equivalent) Proven ability to work across functions: you’ve partnered with Engineering, Product, or Commercial teams and know how to communicate tradeoffs and drive alignmentFamiliarity with, pipeline orchestration (Airflow or similar), model monitoring, CI/CD for analytical workflowsExperience with data visualization tools (Looker, Tableau, or similar) for communicating findings to non-technical stakeholders