Business Intelligence Engineer III

Chewy Chewy · Retail · Louisville, KY +1

This role focuses on building and maintaining data pipelines, data models, and BI solutions for Pharmacy Operations. It involves designing, developing, and operating large-scale data models and reporting mechanisms, ensuring reliable data ingestion and transformation, and delivering self-serve analytics. The role also includes deep-dive analysis, root-cause investigations, and mentoring other analysts.

What you'd actually do

  1. Design, develop, implement, test, document, and operate large-scale data models and BI solutions, including curated datasets, dashboards, and recurring reporting that support Pharmacy Operations.
  2. Build and maintain data ingestion and transformation routines (batch and, where needed, near real-time) using best practices in data modeling and ETL/ELT to ensure reliable, scalable pipelines.
  3. Deliver self-serve reporting and analysis through BI tools and well-structured semantic/abstraction layers that enable consistent metrics across multiple source systems.
  4. Gather business and functional requirements and translate them into robust, scalable, operable solutions that align with broader data architecture and downstream consumption patterns.
  5. Produce high-quality documentation, metadata, and clear metric definitions to improve trust, adoption, and long-term maintainability of Pharmacy Operations analytics products.

Skills

Required

  • SQL
  • Data Modeling
  • ETL/ELT
  • BI Tools (e.g., Tableau)
  • Data Warehousing Concepts
  • Dimensional Modeling
  • Version Control (Git)
  • Cloud Data Warehouse (Snowflake or equivalent)

Nice to have

  • dbt
  • Data Quality Monitoring
  • Alerting
  • Incident Response
  • Python

What the JD emphasized

  • 5+ years of experience in Business Intelligence, Analytics Engineering, or Data Engineering roles delivering analytics solutions (for example dashboards, reporting, and curated datasets) for business teams.
  • Proven experience designing and owning enterprise-grade data pipelines and data models spanning multiple business domains, including complex joins across multiple source systems, incremental processing, and handling late-arriving data.
  • Strong SQL proficiency, including query optimization and building performant data models in a modern cloud data warehouse (Snowflake or equivalent).
  • Solid knowledge of data warehouse concepts and methodologies, including dimensional modeling and designing curated data marts for downstream BI consumption.
  • Experience building governed BI solutions and presenting insights clearly through visualizations (Tableau or comparable BI tool).
  • Experience writing and reviewing version-controlled code (Git or equivalent) and following standards for documentation, testing/validation, and maintainability.
  • Demonstrated ability to establish standards and influence best practices across an analytics team (for example code reviews, modeling conventions, metric governance), without requiring formal people management.