Analytics Engineer

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)

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

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.