Jobs at DoorDash

Design, build, and maintain large-scale backend systems for DoorDash’s logistics marketplace. Responsibilities include defining architecture, improving performance, scalability, reliability, and security, migrating monolithic systems to microservices, and delivering high-impact features. The role involves collaboration with product, design, and engineering teams across Brazil and the United States, as well as participation in technical roadmaps, testing, code reviews, and software releases.

Build and maintain scalable data models, pipelines, aggregation layers, and reporting structures. Collaborate with engineers, data scientists, and stakeholders to translate requirements into reliable analytics solutions. Optimize ETL/ELT processes, define KPIs, ensure reporting quality, automate ad hoc analysis, establish reusable design patterns, and develop high-performing dashboards using tools such as Tableau and Sigma.

Design, build, and maintain large-scale backend systems for DoorDash’s logistics marketplace. Responsibilities include developing scalable and reliable services, contributing to architecture and technical roadmaps, migrating monolith components to microservices, improving performance and security, writing tests, and collaborating in English with product and engineering teams across Brazil and the United States.

Lead a data engineering organization building enterprise-scale data platforms, architectures, pipelines, and reusable data assets. Provide technical vision, improve reliability and development processes, collaborate with stakeholders, and support scalable batch and real-time data solutions. Hire, coach, mentor, and manage engineers while fostering engineering excellence and innovation. The role requires strong system design, data architecture, programming, cloud, orchestration, and large-scale data platform expertise.

Designs and develops large-scale data models, ETL pipelines, data lake and warehouse solutions, quality checks, monitoring, and data products. Partners with business, engineering, product, and third-party stakeholders to gather data requirements. Improves pipeline reliability and scalability, supports reporting and analytics, and helps onboard engineers. The role requires programming, distributed data processing, streaming, database, cloud, orchestration, and reporting-tool expertise.

Develop, release, and operate large-scale backend applications supporting DoorDash’s global logistics marketplace. Define backend architecture and technology stacks, improve system performance, reliability, scalability, and security, and help transition monolithic systems to microservices. The role involves solving complex logistics problems, collaborating cross-functionally, and using AI coding tools throughout the software development lifecycle.

Design, build, and maintain large-scale backend systems for DoorDash’s logistics marketplace. The role involves defining architecture, improving performance and reliability, migrating monolithic systems to microservices, and delivering high-impact features for consumers, Dashers, and merchants. Engineers collaborate across Brazil and the United States, contribute to technical roadmaps, use AI coding tools throughout the software lifecycle, and write tested, scalable code.

Leads and grows data engineering teams while setting technical and strategic direction for enterprise-scale data platforms. Oversees data architecture, reliability, scalability, reusable data assets, ETL orchestration, developer tooling, and engineering excellence. Partners with data scientists, engineers, stakeholders, and external partners to deliver reliable batch and real-time data solutions. Responsibilities include hiring, coaching, performance management, mentoring, strategic planning, and continuous process improvement.

Leads and develops a team of approximately nine engineers, guiding technical execution, architecture, roadmap planning, hiring, and professional growth. Partners with product managers, business leaders, and cross-functional stakeholders to deliver scalable, high-quality backend solutions. The role requires distributed systems expertise, system scaling and performance optimization experience, B2B product development knowledge, API and file-based data integration experience, and strong leadership across remote teams.

Designs and develops large-scale data models, ETL pipelines, data lake and warehouse architectures, and data quality monitoring. Partners with business, engineering, product, and third-party teams to gather requirements and data. Manages data products, improves pipeline reliability and scalability, supports reporting and analytics, and helps onboard engineers. Requires strong programming, SQL, distributed computing, workflow orchestration, streaming, database, cloud, and communication skills.

Lead and grow a backend engineering team responsible for DoorDash’s Credits and Refunds, resolution workflows, and policy configuration platform. Own platform migration, distributed-systems architecture, reliability, scaling, configuration safeguards, and integration of machine-learning models into high-volume production workflows. Partner with Product, ML, Fraud, Data Science, and Operations teams while mentoring engineers, shaping technical direction, improving operational excellence, and supporting engineering recruiting.

Leads and develops a backend engineering team, overseeing roadmap execution, architecture, technical quality, hiring, and professional growth. Partners with product managers, business leaders, and cross-functional stakeholders to deliver scalable solutions. The role requires distributed systems expertise, system scaling and performance optimization experience, B2B product development, API and data integration experience, and the ability to lead remote teams in a fast-paced environment.

Build and maintain scalable data models, pipelines, aggregation layers, and self-service analytics. The role includes optimizing ETL/ELT processes, ensuring data quality and reporting reliability, defining KPIs, automating reporting, and developing dashboard products with tools such as Tableau and Sigma. The engineer will collaborate with data engineers, data scientists, and business stakeholders to deliver analytical solutions across the organization.

Build and scale data models, pipelines, aggregation layers, and self-service analytics. Responsibilities include designing analytical data structures, optimizing ETL/ELT processes, defining KPIs, ensuring reliable reporting, automating ad-hoc analyses, standardizing reporting patterns, and developing dashboards using tools such as Tableau or Sigma. The role collaborates with data engineers, data scientists, and business stakeholders to deliver scalable, high-quality data solutions.

Leads a data engineering team responsible for enterprise-scale data solutions, architecture, reliability, and developer enablement. The role combines people leadership—including hiring, coaching, performance management, and team growth—with technical strategy for scalable data platforms, batch and real-time processing, data assets, and reusable components. Partners cross-functionally to drive engineering excellence, innovation, and long-term platform strategy.

Designs and builds scalable data models, ETL pipelines, data lake and warehouse architectures, data quality checks, monitoring routines, and data products. Collaborates with business, engineering, product, and third-party stakeholders to define and collect requirements. Maintains reliable data infrastructure, supports reporting and analytics use cases, and helps onboard new engineers.