Backend Engineer - Conversations

We're hiring a Staff Engineer - Backend (Data Systems) to own and evolve the data backbone that powers messaging at scale inside High Level's Conversations platform. You'll design, operate, and scale systems that handle billions of documents across Mongo

DB, Firestore, Redis, and Elastic Search with reliability, predictability, and engineering clarity as non-negotiables.

This is a hands‑on IC role you'll code, design, review, and guide. You'll set the standard for how we think about databases, APIs, and engineering craft.

The goal: make our data systems boring in the best possible way, predictable, fast, and easy to trust. Your first project will be to re‑architect and scale Elastic Search to handle billions of documents efficiently while setting best practices for schema design, observability, and testing discipline across the org.

You’ll join the Conversations team, the core communication platform at High Level that powers SMS, Email, Whats App, and DMs for millions of users.

The system processes 2B+ messages monthly, spanning 50+ workloads and thousands of pods across GCP (GKE, Pub/Sub, Cloud Tasks). The data stack includes Mongo

DB, Firestore, Redis, Elastic Search, and Click House, distributed, high-volume, and mission‑critical. This role sits at the intersection of data architecture and engineering culture, scaling systems while shaping how engineers design, test, and reason about them.

• Database architecture:
  Redesign and optimise data models, queries, and indexing strategies across Mongo
  
  DB, Firestore, and Elastic Search.
• Search at scale:
  Own Elastic Search reliability ingestion, indexing, shard strategy, and query performance for billions of documents.
• Reliability and performance:
  Eliminate bottlenecks, improve replication health, and enforce predictable query and index latency.
• System design:
  Define data flow and integration boundaries between storage, cache, and APIs with clear contracts and fault isolation.
• Observability:
  Build visibility into every data path metrics, traces, slow query logs, replication lag, and cluster health dashboards.
• Testing and quality:
  Make testing non‑negotiable, enforce unit, integration, and load testing standards across all backend modules.
• Engineering culture:
  Drive RFCs, ADRs, and design reviews that push clarity and precision. Codify patterns that make good engineering repeatable.
• Hands‑on leadership:
  Write code, design systems, and debug production issues. Lead by technical example, not by delegation.
• Mentorship and influence:
  Level up engineers around you, reviews that teach, feedback that sticks, and systems that outlive individuals.

• 8+ years of backend engineering experience with deep database expertise.
• Proven success with Elastic Search, Mongo
  
  DB, or Firestore at massive scale.
• Strong understanding of indexing, query optimisation, caching, and consistency models.
• Expert in Node.js (Type Script) and comfortable designing scalable microservices.
• Cloud experience with GCP (GKE, Pub/Sub, Cloud Tasks) or similar distributed infra.
• Practical knowledge of observability:
  Grafana, Kibana, Open Telemetry.
• Passion for code quality and process: testing discipline, documentation, and design rigour.
• A track record of shaping team culture, setting standards through RFCs, ADRs, and clear technical writing.
• No tolerance for regressions, unclear ownership, or untested systems.
• Experience with Elastic Search cluster management, multi‑tenant indexing, or lifecycle policies.
• Familiarity with Click House or other OLAP systems for analytics.
• Background in event‑driven systems, data pipelines, or message brokers.
• Contributions to open‑source or public technical writing on database performance or systems design.