Analytics Engineer, Data Science

About the role

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 Team

• Consumer & Growth
• Business Operations
• Dasher & Logistics
• Customer Experience & Integrity
• Merchant
• Ads & Promotions
• New Verticals

Responsibilities

• 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

Requirements

• 2-6+ 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
• Experience 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)
• Strong 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

Qualifications

Preferred qualifications:

• Experience with cloud platforms (AWS, Google Cloud, Azure)
• Experience with machine learning and statistical modeling
• Experience with distributed systems and microservices architecture
• Experience with data storytelling and communication

Skills

• Data engineering
• Data analysis
• Data visualization
• SQL
• Python/Scala
• Tableau/Sigma/Mode
• ETL/ELT
• Data quality checks
• Communication

Benefits

• Comprehensive benefits package including 401(k) with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave
• Medical, dental, and vision benefits
• 11 paid holidays
• Disability and basic life insurance
• Mental health program

Pay

The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.

Schedule

Flexible schedule

Location

Remote jobs associated with the office in NYC only

Contact

To learn more about our benefits, visit our careers page here.

Equal Opportunity Employer

We are committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.