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Salary: USD 100,000 - 125,000 / annual
Gopuff is a rapid-delivery service bringing everyday goods—snacks, household items, beverages, and more—to customers within minutes. The Analytics Engineering team builds the data infrastructure that powers business decisions across the organization.
In this role, you'll serve as the primary analytics engineer for Supply Chain and Merchandising, with secondary support for Marketing and CRM analytics. You'll own the data models and pipelines that inform critical decisions about inventory positioning, demand forecasting, product allocation, vendor performance, and promotional strategy. Your work directly impacts what Gopuff buys, where it's stocked, and how it's promoted.
Key responsibilities include:
- Design, build, and maintain production data models for supply chain and merchandising domains (sales, demand, inventory, damage/expiration, turn, vendor fill rates, purchase orders, allocation).
- Serve as the go-to data expert for these domains, with deep knowledge of the data warehouse and upstream processing layers.
- Partner with Supply Chain, Merchandising, Marketing, CRM, product, and engineering teams to translate business questions into durable, self-serve models and tooling rather than one-off analyses.
- Own data integrity, availability, transformation logic, and efficient access for your domains.
- Build and maintain Looker dashboards and reports used daily by planners and merchants, replacing manual reporting processes.
- Support marketing and CRM analytics work, including campaign performance, promotion lift, and channel reporting.
- Identify data gaps, write data product specifications, and collaborate with engineering to implement proper tracking.
- Automate processes and build testing/monitoring to surface data quality issues before stakeholders encounter them.
- Document models thoroughly so stakeholders can find, understand, and trust data independently.
Minimum Qualifications:
- Bachelor's degree in Engineering, Computer Science, Information Systems, Business, or another quantitative discipline.
- 3+ years building data models integrating complex, disparate data sources using tools such as dbt.
- Expert-level SQL and database table design; ability to write structured, efficient queries against large datasets. Advanced Excel skills for partner collaboration.
- 1+ years building and maintaining reporting and dashboards in Looker or comparable BI tool.
- Strong analytical judgment: ability to move from raw data to clear recommendations and explain implications to business partners.
- Excellent communication skills; ability to translate business needs into tractable work items and explain technical trade-offs to non-technical stakeholders.
- Top-notch organizational skills and ability to manage multiple projects in a fast-paced environment.
Preferred Qualifications:
- Experience with ETL/ELT tooling, particularly dbt.
- Strong knowledge of data warehousing concepts and big data technologies; Snowflake, Redshift, or Azure experience strongly preferred.
- Exposure to supply chain, inventory, merchandise planning, or allocation data (familiarity with model stock, lead time, replenishment cycles, sell-through, turn).
- Experience with marketing or CRM analytics (campaign performance, promotion lift, channel attribution, customer segmentation).
- Experience with demand planning or ERP systems such as JustEnough or Kinaxis.
- Comfort with AI-assisted development tools like Claude for accelerating model development, SQL review, testing, and documentation.
- Alcohol beverage or CPG category experience.
