Software Engineer, Backend

Candidates typically go through three rounds: an initial technical coding and system design interview, a second technical interview focusing on architecture and AI tools, and a final HR interview. The difficulty is moderate to high, with emphasis on real‑world problem solving and design principles. Preparation should include coding practice, system design mock sessions, and familiarity with AI coding tools.

DoorDash fosters a collaborative, fast‑paced culture with a focus on data‑driven decision making. Engineers enjoy opportunities for rapid skill growth, cross‑team collaboration, and a healthy work‑life balance supported by flexible work arrangements.

Bachelor’s or Master’s or Ph.D. in Computer Science or equivalent; 3+ years of experience in software engineering; proficiency in Go, Java, or Python; experience with AI coding tools; background in Big Data infrastructure, cost efficiency, and governance; production‑grade backend experience; strong fundamentals in CS concepts.

Round 1: Technical coding and system design → Round 2: Technical architecture and AI tools → Round 3: HR

DoorDash is a global technology and logistics company that started as a food delivery platform and has expanded into a full‑service marketplace for goods and services. With a mission to empower local economies, DoorDash leverages data, AI, and engineering excellence to deliver reliable, on‑demand logistics at scale. The company’s India team is rapidly growing, building the backbone of its data infrastructure that supports millions of users worldwide. The Software Engineer, Backend role sits on the Data User Platform and Programs team, a founding engineering squad in India. As a key contributor, you will design, build, and operate core services that power the company’s data ecosystem. Your work will directly influence how engineers, analysts, data scientists, and business stakeholders discover, consume, and govern data. Key responsibilities include: 1. Designing and scaling data platform services for reliability, observability, and cost efficiency. 2. Building a unified data discovery and catalog experience that helps users locate datasets, dashboards, and metrics. 3. Developing AI‑enabled assistants and workflows for analytics and operations. 4. Adding monitoring, alerting, and operational tooling to maintain SLAs and reduce incident response time. 5. Driving cost‑efficient data platform design by identifying underutilized resources and encouraging reuse. 6. Instrumenting usage and cost signals into platform services. 7. Supporting safe deprecation and cleanup of stale data assets. 8. Collaborating with product managers, data engineers, and analytics teams to reduce friction across the data ecosystem. 9. Maintaining production‑grade backend systems and ensuring high availability. 10. Mentoring junior engineers and contributing to the team’s technical culture. Tech stack: Go, Java, Python, Big Data infrastructure (Spark, ClickHouse, Iceberg), workflow orchestration (Airflow), AI coding tools (Claude Code, Codex, Cursor), observability and monitoring tools. Growth path: Starting as a founding engineer, you will have the opportunity to shape the platform’s architecture, lead feature teams, and eventually move into senior engineering or technical leadership roles. Why join DoorDash? You’ll gain high ownership, work on cutting‑edge AI and data infrastructure, collaborate with cross‑functional teams, and be part of a fast‑moving, product‑driven environment that rewards innovation and impact.