Implement and optimize data access patterns for efficient interaction with large-scale data using ElasticSearch, Google Firestore, MongoDB Atlas, ClickHouse, and Redis.
Monitor, troubleshoot, and tune existing database instances (SQL, MongoDB, ElasticSearch, ClickHouse) to ensure sub-second latencies and operational stability.
Contribute to the design and implementation of high-performance components that handle terabytes of data.
Focus on instrumentation, benchmarking, and optimizing query paths, indexing, memory/CPU usage, and storage layouts.
Develop and maintain reusable frameworks, SDKs, and platform services in programming languages, with a focus on Node.js and GoLang.
Actively participate in design reviews and adhere to engineering best practices to maintain a high technical standard.
Collaborate with product and platform teams to implement best-practice data-access patterns and uphold SLAs.
Partner with multiple teams to deliver reliable, secure, and maintainable data platform capabilities.
Support the operational health of database environments, including contributing to processes for backup/restore, disaster recovery, security, and compliance across AWS, GCP, and Azure environments.
Requirements
4+ years of software engineering experience, with success in backend services and data-intensive systems.
Mandatory proficiency in Node.js or GoLang for scripting and debugging within our codebase environment.
Hands-on experience optimizing and scaling systems using cloud-managed databases (e.g., MongoDB Atlas) such as ElasticSearch, Firestore, MongoDB, ClickHouse, and Redis.
SDE 2: Proven experience with at least one large-scale database technology.