Senior Backend Engineer, Product and Infra

We're looking for a Senior Backend Engineer to build the systems and services that power our product experience. You'll own the backend infrastructure that makes our content discoverable, our features responsive, and our platform reliable at scale.

Your work will directly shape what users experience: designing APIs that serve rich content, building services that handle real-time interactions, implementing content-matching systems for rights and safety, and ensuring our platform performs under load. You'll architect systems that are fast, correct, and maintainable.

You'll collaborate closely with Product, ML Research, and Mobile/Web teams to ship features that matter. We use Python, Go, BigQuery, Pub/Sub, and a microservices architecture—but we care more about good judgment than specific tool experience.

• →Design and maintain application-level data models that organize rich content into canonical structures optimized for product features, search, and retrieval.
• →Build high-reliability ETLs and streaming pipelines to process usage events, analytics data, behavioral signals, and application logs.
• →Develop data services that expose unified content to the application, such as metadata access APIs, indexing workflows, and retrieval-ready representations.
• →Implement and refine fingerprinting pipelines used for deduplication, rights attribution, safety checks, and provenance validation.
• →Own data consistency between ingestion systems, application surfaces, metadata storage, and downstream reporting environments.
• →Define and track key operational metrics, including latency, completeness, accuracy, and event health.
• →Collaborate with Product teams to ensure content structures and APIs support evolving features and high-quality user experiences.
• →Partner with Analytics and Research teams to deliver clean usage datasets for experimentation, model evaluation, reporting, and internal insights.
• →Operate large analytical workloads in BigQuery and build reusable Dataflow/Beam components for structured processing.
• →Improve reliability and scale by designing robust schema evolution strategies, idempotent pipelines, and well-instrumented operational flows.

• Experience building production backend services and APIs at scale
• Experience building ETL/ELT pipelines, event processing systems, and structured data models for applications or analytics.
• Strong background in data modeling, metadata systems, indexing, or building canonical representations for heterogeneous content.
• Proficiency in Python, Go, SQL, and scalable data-processing frameworks (Dataflow/Beam, Spark, or similar).
• Familiarity with BigQuery or other analytical data warehouses and strong comfort optimizing large queries and schemas.
• Experience with event-driven architectures, Pub/Sub, or Kafka-like systems.
• Strong understanding of data quality, schema evolution, lineage, and operational reliability.
• Ability to design pipelines that balance cost, latency, correctness, and scale.
• Clear communication skills and an ability to collaborate closely with Product, Research, and Analytics stakeholders.

• Experience building application-facing APIs or microservices that expose structured content.
• Background in information retrieval, indexing systems, or search infrastructure.
• Experience with fingerprinting, perceptual hashing, audio similarity metrics, or content-matching algorithms.
• Familiarity with ML workflows and how downstream analytics and usage data feed back into research pipelines.
• Understanding of batch + streaming architectures and how to blend them effectively.
• Experience with Go, Next.js, or React Native for occasional full-stack contributions.