Samba’s Product Engineering team builds the software that puts our data to work — customer-facing platforms, internal tooling, and the APIs and services that connect them. Our engineers own meaningful systems end-to-end, ship production code every week, and work directly with product, data science, and go-to-market teams to deliver outcomes that matter.
As a Full Stack Engineer, you will own features and systems across the stack — from web frontends to backend services, data pipelines, and cloud infrastructure. The backend work here is not just CRUD: it spans analytical SQL over large-scale TV viewership datasets, Firestore-backed caching pipelines, a multi-cloud environment (GCP and AWS), and a non-trivial auth model. We care about engineers who think in systems, take ownership of correctness and reliability, and are comfortable doing the archaeology that real production codebases require.
What You'll Do:
- Own features end-to-end — frontend interfaces, backend services and APIs, data models, and the infrastructure that runs them
- Write and maintain analytical SQL over large-scale datasets (BigQuery); understand the domain well enough to extend measurement logic correctly
- Design and operate data pipelines and caching layers that sit between raw data and the product surface
- Maintain and evolve the auth and authorization model across Firebase, Auth0, and Firestore security rules
- Manage multi-cloud integrations across GCP (BigQuery, Cloud Functions, Firestore, Cloud Storage) and AWS (S3)
- Hold a high bar for testing, observability, and reliability — you instrument what you ship and own its behavior in production
- Participate in architecture reviews, contribute to the technical roadmap, and mentor junior engineers
Who you are:
- 2+ years of experience building and operating production software
- Strong command of TypeScript or JavaScript across frontend and backend
- Experience building backend services and APIs — RESTful design, authentication patterns, token-based auth flows
- Comfortable writing non-trivial SQL — window functions, aggregations, query optimization; BigQuery or similar analytical datastore experience a plus
- Hands-on experience with cloud infrastructure: serverless or managed compute, object storage, secret management, scheduled jobs
- Familiarity with eventual consistency and cache invalidation patterns in distributed systems
- Proficient in agentic development — building or integrating LLM-powered workflows, tool-use patterns, or AI agents in production
- Comfortable doing archaeology in production codebases — reading unfamiliar code, identifying live vs. legacy paths, and making safe changes