Support Solutions Engineer (l5), Graph Search

Netflix Netflix · Big Tech · United States · Remote · Engineering Operations

Netflix is seeking a Support Solutions Engineer to join their Engineering Support Organization. This role focuses on providing excellent support to Netflix's developer community, troubleshooting issues, automating support needs, and improving the usability of the Graph Search platform. The ideal candidate will have experience in customer-facing engineering support, knowledge of search platforms, data indexing pipelines, and distributed systems, and be adept at problem-solving and technical communication.

What you'd actually do

  1. monitoring and handling our customers’ requests, troubleshooting, solving issues, automating support needs, developing support documentation and runbooks, improving and maintaining support tools and automation, understanding our product offerings, and continuously looking for ways to improve the engineering support experience.
  2. writing and building a comprehensive self-service knowledge base
  3. understand our complex offerings on a technical level, be hands-on in the development of our support automation tooling, and recommend product and operational improvements based on customer interactions.
  4. diagnose why data isn't appearing in an index, interpret document count discrepancies, and reason through reindexing and refresh workflows.
  5. debug query issues such as unexpected results, unindexed field errors, and schema federation mismatches.

Skills

Required

  • customer support
  • troubleshooting
  • automation
  • documentation
  • search engine concepts (index mappings, text analyzers, aliases, data backfill processes, index lifecycle management)
  • OpenSearch or Elasticsearch
  • GraphQL schemas
  • debugging query issues
  • platform configuration debugging
  • event-driven architectures
  • message queue concepts
  • dead-letter queue (DLQ) patterns
  • Kafka, RabbitMQ, AWS SQS/SNS
  • access control models (RBAC, ABAC)
  • distributed traces
  • structured logs
  • monitoring dashboards
  • SQL
  • test and production environment reasoning

Nice to have

  • GraphQL server framework (Apollo, Spring GraphQL, or similar)
  • Datadog, Jaeger, Grafana, Splunk, or similar

What the JD emphasized

  • Graph Search platform
  • search technologies
  • developer experience
  • operational excellence
  • search platforms
  • data indexing pipelines
  • distributed systems
  • search engine concepts
  • GraphQL
  • debugging platform configuration
  • event-driven architectures
  • access control models
  • distributed traces