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The Core BI team at DoorDash (which includes Wolt and Deliveroo) builds and operates the backend services, integrations, and automation that power business intelligence across the group. As a Software Engineer on this team, you will design, build, test, deploy, and operate backend services, APIs, and infrastructure that BI platforms depend on.
Key responsibilities include:
- Design and operate backend services, APIs, and automation supporting BI platforms (primarily Looker and Sigma)
- Automate the platform lifecycle end-to-end: provisioning, metadata management, permissions, migrations, archival, and validation
- Build integrations between BI platforms and the wider ecosystem (data warehouses, identity providers, orchestration, CI/CD, internal developer tooling)
- Improve availability, observability, performance, scalability, and security of systems you own
- Incorporate AI tooling into your engineering practice and build LLM-backed capabilities where appropriate
- Raise the engineering bar through service design, code review, testing, CI/CD, documentation, and developer experience improvements
- Own problems end-to-end from discovery through design, implementation, deployment, and operational support
- Work closely with Data Engineers, Analytics Engineers, Data Scientists, Product Managers, and business teams
This is a hands-on software and platform engineering role focused on backend and platform problems in the BI domain. You will be deeply embedded across multiple domains and expected to operate what you build in production.
Requirements:
- 3+ years of professional software engineering experience building and operating production backend, platform, or infrastructure systems
- Proficiency in Python with readable, maintainable, well-tested code; comfort with SQL and working understanding of data modeling and warehousing concepts
- Experience building and owning APIs, integrations, or automation in production with sound judgment on service boundaries, authentication, data contracts, and failure modes
- Hands-on experience with CI/CD, containers, Kubernetes, observability, debugging, and incident response; expectation to operate what you build
- Hands-on experience using AI tools (LLMs, agentic workflows, AI-assisted development) as part of your engineering practice with judgment about where they help
- End-to-end ownership of ambiguous problems, clear communication with technical and non-technical teams, and comfort self-organizing in a fast-paced distributed environment
Nice to have:
- Experience owning or integrating with BI platforms (Looker, Sigma, or comparable tools) and familiarity with semantic layers (LookML, dbt)
- Experience automating identity and access through Okta, SCIM, role-based access controls, or building multi-tenant platforms across brands and regions
- Experience shipping LLM-backed features to real users (retrieval, grounding, evaluation) or with MCP, agent frameworks, or tool-calling in production
