Staff/Senior Analytics Engineer (Data Science & Analytics)

Simbe, Inc.; San Francisco (CA); On-site; USD 120,000 - 210,000; Full time

Benefits offered by this job

Comprehensive health plans

Culture of learning

Flexible time off

Job summary

Simbe, Inc. is seeking an Analytics Engineer to own production-grade data pipelines, from ideation to delivery, partnering with Product, Engineering and Data Scientists to surface insights at scale.

You will build data marts for self-serve analytics, shape data with Kimball dimensional modeling, and leverage dbt to deliver robust analytics features. This role requires cross-functional collaboration and a hands-on approach to AI-assisted workflows.

Qualifications

• Experience owning full analytics feature lifecycles from scoping to shipping.
• Proven ability to work across Engineering, Product, and Commercial teams.
• Strong SQL proficiency and experience with large-scale cloud data platforms.

Responsibilities

• Own production analytics pipelines end-to-end, from design to production"
• Establish organized data marts to enable self-serve analytics and AI insights.
• Translate retail data into actionable business decisions by connecting signals to outcomes.
• Drive cross-functional delivery by aligning stakeholders and removing blockers.
• Apply AI tooling to accelerate analytics work using LLMs and agents.
• Raise standards for reproducibility, documentation, and code quality.

Skills

SQL

Python

AI tooling

Prompt Engineering

LLM APIs

Cross-functional collaboration

Data modeling

Data visualization

Tools

BigQuery

Airflow

dbt

Looker

Tableau

CI/CD

Job description

• 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)

Benefits

• Comprehensive 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 workflow5+ 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