Analytics Engineer & Data Scientist: Scale Data Foundations

DoorDash; San Jose (CA); On-site; USD 118,000 - 257,000; Full time

Benefits offered by this job

401(k) plan with employer matching

16 weeks of paid parental leave

wellness benefits

commuter benefits match

paid time off and paid sick leave

Job summary

DoorDash’s Analytics Engineering team builds scalable data foundations to enable fast, reliable insights across Product, Operations, Finance, and more. As an Analytics Engineer, you’ll scale data products and drive end-to-end analytics initiatives with Data Engineers, Data Scientists, Software Engineers, Product Managers, and Operators.

This highly technical role centers on delivering trusted data and metrics, embedded across domains, to support decision-making at all levels of the company.

Qualifications

• 2–6+ years of experience in BI, analytics engineering, data engineering, or similar role.
• Strong proficiency in SQL for data transformation; Python or Scala experience.
• Experience creating reporting and data visualization solutions with Looker/Tableau/Sigma.

Responsibilities

• Translate business needs into data requirements with stakeholders.
• Develop structured data solutions to answer key business questions.
• Lead data product development and self‑serve analytics tools at scale.
• Build canonical datasets via high‑volume ETL/ELT pipelines and data lake/warehouse concepts.
• Design metrics and dashboards with Tableau, Sigma, and Mode.
• Uphold data integrity standards to improve reusability and standardization.

Skills

SQL

Python

Scala

Communication skills

Education

Relevant degree in Math/Physics/Statistics/Economics/Computer Science

Tools

Tableau

Sigma

Mode

Looker

S3

Trino

Hive

Spark

Pydeequ

Great Expectations

Job description

DoorDash’s Analytics Engineering team builds scalable data foundations to enable fast, reliable insights across Product, Operations, Finance, and more. As an Analytics Engineer, you’ll scale data products and drive end-to-end analytics initiatives with Data Engineers, Data Scientists, Software Engineers, Product Managers, and Operators.

This highly technical role centers on delivering trusted data and metrics, embedded across domains, to support decision-making at all levels of the company.