Analytics Engineer

Responsibilities

• Design, develop, and maintain robust data models to support analytical and product data needs
• Collaborate with data engineers, data scientists, and business stakeholders to translate requirements into scalable solutions
• Implement and optimize ETL/ELT processes to ensure data quality and performance
• Own and define business KPIs, measurement plans, and reporting requirements
• Build processes to ensure correct, timely, and reliable reporting
• Address ad-hoc reporting requirements and find pathways for automation
• Build and enforce common design patterns to increase report reusability and standardization
• Build visually appealing, high-performing reporting/dashboard products using tools like Tableau or Sigma

Requirements

• 3+ years of experience in business intelligence, data analytics, or data engineering
• Strong SQL skills and experience with data modeling techniques (e.g., dimensional modeling, 3 Nf, data vault)
• Proficiency in Python or Scala
• Experience building reporting and dashboarding solutions using data lake/Snowflake or similar ecosystems
• Expertise in database fundamentals, SQL, and performance tuning
• Excellent communication skills for working with technical and non-technical teams
• Ability to work in a fast-paced environment as a self-starter
• Ability to think strategically and interpret market and consumer information
• Fluency in English for interviews

Preferred Qualifications

• Experience with real-time data processing and streaming technologies
• Experience with modern data warehousing platforms like Snowflake, Databricks, or Redshift
• Knowledge of data visualization tools such as Looker or Tableau
• Familiarity with machine learning concepts and their data requirements

About the Company

DoorDash is building the world’s most reliable on-demand logistics platform. We are a technology and logistics company that empowers local economies, helping people get any and all goods delivered to their doors.