Analytics Engineer, Gopuff

• Bachelor's in Engineering, Computer Science, Information Systems, Business, or another quantitative discipline
• 3+ years of experience building data models that integrate complex and disparate data sources, using tools such as dbt
• Expert in SQL and database table design, able to write structured and efficient queries against large datasets. Advanced Excel skills for partner collaboration
• 1+ years building and maintaining reporting and dashboards in Looker or a comparable BI tool
• Strong analytical judgment: able to move from raw data to a clear recommendation, and to explain the 'so what' to business partners who will act on it
• Excellent communication skills, with the ability to translate business needs into tractable work items and to explain technical trade-offs to non-technical partners
• Top-notch organizational skills and the ability to manage multiple projects in a fast-paced environment
• Move fast, be a team player, always be learning, and give back

Desirable

• As an Analytics Engineer at Gopuff, you'll build and maintain the bridge between our data and the rest of the organization.
• This role sits on the Analytics Engineering team and is dedicated to our Supply Chain and Merchandising partners, with a secondary focus on marketing and CRM analytics.
• You'll own the models that our planning, allocation, and merch teams use to decide what we buy, where we place it, and how we promote it, and you'll be accountable for the integrity, reliability, and usability of that data
• Design, build, and maintain the production data models that power supply chain and merchandising decisions: sales and demand, inventory position and in-stock, damage and expiration, turn, vendor fill rate, purchase orders, and allocation
• Be the go-to data expert for these domains, with a deep understanding of our data warehouse and the processing layers feeding it
• Partner with Supply Chain divisional teams, Merchandising, Marketing, CRM, product managers, and engineers to translate business questions into durable models and self-serve tooling rather than one-off pulls
• Own data integrity, availability, transformation logic, and efficient data access for the domains you support
• Build and maintain reporting and dashboards in Looker that planners and merchants use daily, and retire the manual reporting they replace
• Support marketing and CRM analytics alongside the supply chain work: campaign and promotion performance, channel reporting
• Identify gaps in existing data, write data product specs, and work with engineering teams to get the right tracking in place
• Automate wherever possible, and build testing and monitoring so data quality problems surface before stakeholders find them
• Document your models so every stakeholder can find, understand, and trust the data without asking you first