Analytics Engineer

DoorDash; San Francisco (CA); On-site; USD 120,000 - 150,000; Full time

Benefits offered by this job

401(k) with employer matching

16 weeks paid parental leave

Wellness benefits

Job summary

DoorDash is hiring an Analytics Engineer in San Francisco to build and scale data foundations that drive insights across the organization. The ideal candidate will collaborate with various teams to translate business needs into data solutions and lead the development of self-serve analytics tools.

Successful candidates will possess strong SQL skills and 3+ years of experience in analytics or engineering. Comprehensive benefits include flexible paid time off, 401(k) matching, and equity opportunities.

Qualifications

• 3+ years of experience in business intelligence, analytics engineering, or data engineering.
• Strong SQL and familiarity with Python or Scala.
• Expertise in data visualization and dashboarding.

Responsibilities

• Collaborate with teams to understand business needs and data requirements.
• Build and maintain ETL/ELT pipelines and canonical datasets.
• Design metrics and data visualizations to provide insights.

Skills

SQL proficiency

Python/Scala proficiency

Data visualization tools

Data quality checks

Excellent communication skills

Analytical thinking

Education

3+ years in business intelligence or related fields

Tools

Tableau

Looker

Airflow

Job description

About The Team

The Analytics Engineering team at DoorDash is embedded within the Analytics and Data Engineering Orgs. It builds internal data products that scale decision‑making across business teams and drive operational efficiency. Data is fundamental to DoorDash’s success, and this team enables high‑impact, data‑driven solutions across Product, Operations, Finance, and more.

About The Role

As an Analytics Engineer, you’ll build and scale the data foundations that enable fast, reliable, and actionable insights. You’ll work closely with partner teams across Data Engineering, Data Science, Software Engineering, Product Management, and Operations to drive end‑to‑end analytics initiatives. This highly technical role requires solving complex data problems and deeply embedding in multiple domains.

Key Responsibilities

• Collaborate with data scientists, data engineers, and business stakeholders to understand business needs and translate scope into data requirements.
• Identify key business questions, build structured solutions, and generate insights.
• 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 such as Tableau, Sigma, and Mode.
• Champion high data integrity standards to increase reusability, readability, and standardization.

Required Qualifications

• 3+ years of experience in business intelligence, analytics engineering, data engineering, or a similar role.
• Strong proficiency in SQL for data transformation and proficiency 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 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 a fast‑paced environment, self‑starter, and self‑organizing.
• Ability to think strategically, analyze and interpret market and consumer information.
• Comfortable exercising discretion and independent judgment in performing job duties, including evaluating options and determining appropriate courses of action within the scope of assigned responsibilities.

Nice to Have

• Experience with modern data warehousing platforms (e.g., Snowflake, Databricks, Redshift) and performance optimization.
• Experience building multi‑step ETL jobs and orchestrating workflows (e.g., Airflow, Dagster, DBT).
• Familiarity with experimentation concepts such as A/B testing and their data requirements.

Compensation

The successful candidate’s starting pay will fall within the pay range below and is determined based on job‑related factors including skills, experience, qualifications, work location, and market conditions. Base salary is localized to the employee’s work location. In addition to base salary, the role includes opportunities for equity grants. DoorDash cares about you and offers a comprehensive benefits package, including a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off, paid sick leave, 11 paid holidays, disability and basic life insurance, family‑forming assistance, and a mental health program.

Paid Time Off Details

• 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., ~6.7 hours/month at 40 hours/week) and paid sick time accrued at 1 hour for every 30 hours worked (e.g., ~5.8 hours/month at 40 hours/week).

Diversity, Equity, and Inclusion

We are committed to creating an inclusive community. No employee or applicant will face discrimination or harassment based on race, color, ancestry, national origin, religion, age, gender, marital/domestic partner status, sexual orientation, gender identity or expression, disability status, or veteran status. We also strive to prevent other forms of inappropriate behavior. All qualified applicants are encouraged to apply.

Notice for NYC Applicants

Applicants for jobs located in NYC or remote jobs associated with an office in NYC are subject to the New York City Administrative Disabilities and Equity Act (AEDT) considerations.