Job Description:
Our Opportunity
Chewy is seeking a Business Intelligence Engineer III to join the Fulfillment Center Technology Analytics team. The team is focused on scalable product analytics, AI-enabled inspection tools and proactive operational decision support across Chewy's fulfillment network.
This is a hands-on senior technical role. The successful candidate will design and build complex analytics and applied AI solutions, set engineering standards for the team, and partner closely with Product, Engineering, Data Science and Operations.
What You'll Do
- Lead complex, multi-domain analyses of fulfillment center performance, including efficiency, throughput, capacity, labor productivity and quality.
- Build reusable analytics products, inspection tools, automated root-cause analysis and self-service capabilities that help Operations and Product teams manage the business proactively.
- Apply AI, machine learning, agentic workflows, retrieval-augmented generation and predictive analytics to operational problems, taking solutions from discovery and validation through production adoption.
- Design scalable, tested and well-documented data models and pipelines, with strong data quality, observability and production readiness.
- Own analytics initiatives end to end, from problem definition and metric design through development, deployment, adoption and measurement of business impact.
- Raise the team's engineering bar through design and code reviews, shared standards and reusable components adopted by adjacent teams.
- Mentor junior BI engineers and foster a culture of experimentation, disciplined validation and reuse.
- Communicate findings, tradeoffs and recommendations clearly to technical teams, operational partners and senior leaders.
What You'll Need
- Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, Information Systems or a related field.
- 5+ years of experience in business intelligence, analytics engineering, data engineering or applied AI/ML.
- Strong technical depth in SQL, Python, data modeling, ETL/ELT and cloud data platforms such as AWS and Snowflake.
- Experience with modern data transformation and testing tools such as dbt.
- Practical experience applying AI/ML to analytics or operational workflows, such as LLMs, agents, RAG, evaluation frameworks or predictive models.
- Experience building analytics applications or visualizations using tools such as Streamlit, Plotly Dash, React or Tableau.
- Solid software engineering practices, including source control, modular design, testing, CI/CD and monitoring.
- Proven ability to work through ambiguity, define the right problem and deliver scalable solutions tied to business outcomes.
- Strong written and verbal communic