Latamcent·6 days ago
SourceFuse is looking for a Go Backend Engineer to join the team building the execution layer of a high-throughput data platform. This is a high-impact, technically demanding role where you will own the core streaming and data processing infrastructure — from Kafka-based ingestion through windowed aggregation, KPI computation, and time-series storage.
You will work on systems that process millions of data points every 15 minutes, where performance, reliability, and correctness are non-negotiable. The ideal candidate brings deep Go expertise, hands-on Kafka experience in high-throughput environments, and the distributed systems mindset to deliver production-grade pipelines independently — with zero REST API surface. Everything here is event-driven, internal, and pipeline-first.
In the first 3–6 months, success means:
Own and deliver high-performance Kafka consumers/producers in Go, meeting throughput and latency requirements
Implement windowed aggregation, state handling, and idempotent writes to TSDB without requiring daily oversight
Build out adapters for DB/API/SFTP ingestion with clean retry and DLQ strategies
Contribute to observability infrastructure and establish profiling baselines
Deliver against project milestones in a fast-paced Silicon Valley startup environment
Integrate smoothly with a cross-functional, globally distributed team (US + Asia time zones)
Build high-performance Kafka consumers and producers in Go for a high-throughput data platform
Implement windowed aggregation and state handling for real-time streaming pipelines
Design and implement retry logic and dead letter queue (DLQ) strategies to ensure data reliability
Ensure idempotent writes to time-series databases (TSDB — cloud-native, e.g. ADX, Snowflake)
Build adapters for DB, API, and SFTP-based data ingestion
Implement dynamic configuration management using CRD watcher patterns
Write production-grade, secure code following performance profiling and optimization best practices
Work within a fully cloud-native Kubernetes environment (Azure-first, expanding to AWS/GCP)
Collaborate with cross-functional teams across different cultures, organizations, and time zones
4–8 years of overall backend engineering experience
3+ years of hands-on Go development in production environments
Strong knowledge of Go concurrency patterns: goroutines, channels, and sync primitives
Kafka integration experience in high-throughput, event-driven distributed systems (Avro/REST schema, performance tuning)
Docker and Kubernetes proficiency — cloud-managed environments (Azure, AWS, or GCP)
Experience building and maintaining data pipelines and event-driven architectures — not REST API-only profiles
Observability instrumentation (logging, metrics, tracing)
Secure coding practices and performance profiling experience
Strong distributed systems fundamentals
Experience working with high-throughput, high-volume data at scale (e.g. IoT, fintech, adtech, large-scale monitoring, or similar domains)
Excellent communication skills in English — able to articulate technical decisions clearly under pressure
Self-directed and delivery-oriented; able to operate in fast-paced startup environments with shifting requirements
English fluency: C1 or higher (assessed under realistic working conditions)
Must overlap with PST (Pacific Standard Time) working hours
Experience with large-scale monitoring/observability platforms or high-throughput data systems (highly preferred)
Time-series database experience — ADX (Azure Data Explorer) or Snowflake (highly preferred)
Event-driven architecture depth (highly preferred)
Experience with streaming systems (Flink, Spark Streaming, or similar)
Familiarity with telecom or IoT network data semantics
Experience in platform or SaaS control planes
Background working with Silicon Valley or US-based startup teams
REST API-only Go engineers with no data pipeline or event-driven architecture experience
CRUD-only backend engineers without distributed systems exposure
Node-only engineers unfamiliar with distributed system design
Go engineers with no Kafka or Kubernetes production experience
Data engineers limited to Spark/Hadoop batch processing
DevOps-focused engineers without system design depth
Engineers resistant to or unfamiliar with cloud-native environments
Remote, independent contractor role
Location: Latin America (Argentina, Brazil, Colombia, Peru preferred)
Time Zone: PST overlap required
Compensation: USD/month, based on experience
Equipment: Candidate provides own device; SourceFuse provides software access
PTO: 15 days (after 90-day onboarding period) + ~8 national holidays
L&D budget available after 6 months
Engagement: 9–12 months, with potential for reassignment to other projects
SourceFuse is a global cloud-native technology company helping businesses evolve through digital transformation. With 550+ employees and 20+ years of experience, SourceFuse operates across the USA, UK, Japan, India, and Australia. The company is HIPAA compliant and ISO 27001 certified, serving clients across industries that require enterprise-grade security, scalability, and reliability.