Analytics Engineer
Analytics Engineer at DoorDash in São Paulo who designs and maintains data models, ETL/ELT pipelines, and self-service dashboards (Tableau/Sigma, Snowflake) to power reporting and KPI measurement across the company.
- Compensation
- Not disclosed
- Location
- São Paulo, Brazil
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Data analytics
- Posted
Skills
Must have
- 3+ years experience in business intelligence, data analytics, data engineering or a similar role
- Strong SQL skills and experience with data modeling techniques (e.g., dimensional modeling, 3NF, data vault)
- Proficiency in a programming language such as Python or Scala
- Experience building reporting and dashboarding solutions using data lake/Snowflake or similar ecosystem
- Expert in database fundamentals, SQL and performance tuning
- 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
- Interviews will be conducted in English
Nice to have
- Experience with real-time data processing and streaming technologies
- Experience with modern data warehousing platforms (e.g., Snowflake, Databricks, Redshift) and data visualization tools (e.g., Looker, Tableau)
- Familiarity with machine learning concepts and their data requirements
Full description
Engineering the future of logistics – from Brazil to the world
About the Team
DoorDash is building the world’s most reliable on-demand logistics platform. Brazil is a strategic and growing engineering hub for DoorDash. Based in São Paulo, our teams build and scale systems that power millions of users globally. This is an opportunity to shape world-class logistics technology while growing your career in Brazil.This is a unique opportunity to join one of Silicon Valley’s fastest-growing companies, while staying close to home.
Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing dashboards, data structures, and data warehouse architecture; this team serves as the foundation for decision-making at DoorDash.
About the Role
DoorDash is looking for an Analytics Engineer to build and scale data models, pipelines, and self-service analytics across the organization. In this role, you’ll focus on developing a reliable aggregation layer and reporting structure that meets our growing business needs, enabling teams to access and analyze data independently.
You’re excited about this opportunity because you will…
- Design, develop, and maintain robust data models to support analytical and product data needs across the organization
- Collaborate with data engineers, data scientists, and business stakeholders to understand data requirements and translate them into scalable data solutions
- Implement and optimize ETL/ELT processes to ensure data quality, reliability, and performance
- Own and define business KPIs, their measurement plans, data requirements and reporting
- Build processes to ensure correct, timely and reliable reporting
- Address ad-hoc reporting requirements and find pathways for automation
- Build and enforce common design patterns to increase report reusability, readability and standardization
- Build visually appealing, high-performing, and impactful reporting/dashboard products using tools like Tableau/Sigma across large data sets
Interviews will be conducted in English
We’re excited about you because…
- 3+ years experience working in business intelligence, data analytics, Data engineering or a similar role
- Strong SQL skills and experience with data modeling techniques (e.g., dimensional modeling, 3 Nf, data vault)
- Proficiency in a programming language such as Python or Scala
- Experience building reporting and dashboarding solutions using data lake/Snowflake or similar ecosystem