Senior Analytics Engineer

Overview

Build and scale data models, pipelines, and self-service analytics across DoorDash, with a focus on a reliable semantic/presentation layer and reporting structure.

What you'll do

• Design, develop, and maintain robust data models to support analytical and product data needs across the organization
• Collaborate with data engineers, data scientists, and business stakeholders to translate data requirements into scalable data solutions
• Implement and optimize ETL/ELT processes to ensure data quality, reliability, and performance
• Own and define business KPIs, their measurement plans, data requirements and reporting
• 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, readability and standardization
• Build visually appealing, high-performing, and impactful reporting/dashboard products using tools like Sigma/Thoughtspot/Looker across large data sets

What you'll need

• 5+ years of extensive experience working in business intelligence, data analytics, data engineering or a similar role
• Strong SQL skills and experience with data modeling techniques (e.g., dimensional modeling, 3NF, data vault)
• Proficiency in a programming language such as Python or Scala
• Experience building reporting and dashboarding solutions using data lake/Snowflake or similar ecosystem
• Expert in database fundamentals, SQL and performance tuning
• Excellent communication skills and experience working with technical and non-technical teams
• Comfortable working in a fast-paced environment, self-starter and self-organizing
• Ability to think strategically, analyze and interpret market and consumer information

Nice to have

• Experience with real-time data processing and streaming technologies
• Experience with modern data warehousing platforms (e.g., Snowflake, Databricks, Redshift) and knowledge of data visualization tools (e.g., Looker, Tableau)
• Familiarity with machine learning concepts and their data requirements