Analytics Engineer

DoorDash USA-posted 2 days ago

Full-time • Mid Level

San Francisco, WA

5,001-10,000 employees

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About the Team The Analytics Engineering team at DoorDash is embedded within the Analytics and Data Engineering Orgs, and is responsible for building internal data products that scale decision-making across business teams and drive efficiency in our operations. Data is fundamental to DoorDash’s success, and this team plays a critical role in enabling high-impact, data-driven solutions across Product, Operations, Finance, and more. About the Role As an Analytics Engineer, you’ll play a key role in building and scaling the data foundations that enable fast, reliable, and actionable insights. You’ll work closely with partner teams to drive end-to-end analytics initiatives; working alongside Data Engineers, Data Scientists, Software Engineers, Product Managers, and Operators. This is a highly technical role where you'll be a driving force behind the analytics stack, delivering trusted data and metrics that support decision-making at all levels of the company. If you're energized by solving technical problems with data and comfortable being deeply embedded across several domains, this role is for you!

Collaborate with data scientists, data engineers, and business stakeholders to understand business needs, and translate that scope into data requirements
Identify key business questions and problems to solve for, and generate insights by developing structured solutions to resolve them
Lead the development of data products and self-serve tools that enable analytics to scale across the company
Build and maintain canonical datasets by developing high-volume, reliable ETL/ELT pipelines using data lake and data warehousing concepts
Design metrics and data visualizations with dashboarding tools like Tableau, Sigma, and Mode
Be a cross-functional champion at upholding high data integrity standards to increase reusability, readability and standardization

3+ years of experience working in business intelligence, analytics engineering, data engineering or a similar role
Strong proficiency in SQL for data transformation, comfort in at least one functional/OOP language such as Python or Scala
Expertise in creating compelling reporting and data visualization solutions using dashboarding tools (e.g., Looker, Tableau, Sigma)
Familiarity with database fundamentals (e.g. S3, Trino, Hive, Spark), and experience with SQL performance tuning
Experience in writing data quality checks to validate data integrity (e.g., Pydeequ, Great Expectations)
Excellent communication skills and experience working with technical and non-technical teams
Comfortable working in fast paced environment, self starter and self organizing
Ability to think strategically, analyze and interpret market and consumer information
Must be comfortable regularly exercising discretion and independent judgment in performing job duties, including evaluating options, making informed decisions, and determining appropriate courses of action within the scope of assigned responsibilities.

Experience with modern data warehousing platforms (e.g., Snowflake, Databricks, Redshift) and ability to optimize performance
Experience building multi-step ETL jobs coupled with orchestrating workflows (e.g. Airflow, Dagster, DBT)
Familiarity with experimentation concepts like A/B testing and their data requirements

DoorDash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act).
DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others.
To learn more about our benefits, visit our careers page here .
For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.
For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week).

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