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Staff Backend Engineer - Conversations
- New York, New York, United States
- New York, New York, United States
À propos
Our people With over 2,000 team members across 10+ countries, HighLevel operates as a global, remote-first organization built for speed and ownership. We value initiative, clarity and execution, creating space for ambitious people to build systems that support millions of businesses worldwide. Here, innovation thrives, ideas are celebrated and people come first, no matter where they call home.
Our impact Every month, HighLevel enables more than 1.5 billion messages, 200 million leads and 20 million conversations for the more than 1 million businesses we support. Behind those numbers are real people building independence, expanding opportunity and creating measurable impact. We’re proud to be a part of that.
Role Summary We’re hiring a Staff Engineer – Backend (Data Systems) to own and evolve the data backbone that powers messaging at scale inside HighLevel’s Conversations platform.
You’ll design, operate, and scale systems that handle billions of documents across MongoDB, Firestore, Redis, and ElasticSearch — 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 ElasticSearch to handle billions of documents efficiently while setting best practices for schema design, observability, and testing discipline across the org.
Team & Project Overview You’ll join the Conversations team — the core communication platform at HighLevel that powers SMS, Email, WhatsApp, 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 MongoDB, Firestore, Redis, ElasticSearch, and ClickHouse — 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.
Responsibilities
Database architecture: Redesign and optimize data models, queries, and indexing strategies across MongoDB, Firestore, and ElasticSearch
Search at scale: Own ElasticSearch reliability — ingestion, indexing, shard strategy, and query performance for billions of documents
Reliability & 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 & 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 & influence: Level up engineers around you — reviews that teach, feedback that sticks, and systems that outlive individuals
Requirements
8+ years of backend engineering experience with deep database expertise
Proven success with ElasticSearch, MongoDB, or Firestore at massive scale
Strong understanding of indexing, query optimization, caching, and consistency models
Expert in Node.js (TypeScript) and comfortable designing scalable microservices
Cloud experience with GCP (GKE, Pub/Sub, Cloud Tasks) or similar distributed infra
Practical knowledge of observability: Grafana, Kibana, OpenTelemetry
Passion for code quality and process: testing discipline, documentation, and design rigor
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
Nice to Have
Experience with ElasticSearch cluster management, multi‑tenant indexing, or lifecycle policies
Familiarity with ClickHouse 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
EEO Statement The company is an Equal Opportunity Employer. As an employer subject to affirmative action regulations, we invite you to voluntarily provide the following demographic information. This information is used solely for compliance with government recordkeeping, reporting, and other legal requirements. Providing this information is voluntary and refusal to do so will not affect your application status. This data will be kept separate from your application and will not be used in the hiring decision.
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Compétences linguistiques
- English
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