SourceFuse

Technology

SeniorGoBackendEngineer

₹25–45L ~AI est. Argentina FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Go Backend Engineer at SourceFuse. Skills: Go Backend, Kafka, Distributed Systems, Data Pipelines. Own and deliver Kafka consumers/producers. Implement windowed aggregation”

What You'll Achieve.

Meet throughput requirements; Meet latency requirements; Deliver production-grade pipelines

Industry & Context.

Technology
Problems you'll solve

Root cause analysis

Eligibility Requirements

PST overlap required

What They're Looking For.

Must Have

4-8 years backend engineering, 3+ years Go development, Go concurrency patterns, Kafka integration experience, Docker and Kubernetes proficiency, Data pipelines experience, Observability instrumentation, Secure coding practices, Performance profiling experience, Distributed systems fundamentals, Telecom-grade data experience, Excellent English communication, Self-directed and delivery-oriented, PST working hours overlap, English fluency C1

Nice to Have

Telecom experience preferred, Large-scale monitoring experience, Observability platforms experience, Time-series database experience, ADX experience preferred, Snowflake experience preferred, Event-driven architecture depth, Streaming systems experience, GRPC services in Go, Telecom network data semantics, Multi-cloud architecture experience, Platform or SaaS control planes, US-based startup teams experience

What You'll Do.

Own and deliver Kafka consumers/producers

Implement windowed aggregation

Implement state handling

Implement idempotent writes

Build ingestion adapters

Contribute to observability infrastructure

Establish profiling baselines

Deliver against project milestones

Integrate with cross-functional teams

Build Kafka consumers and producers

Design dead letter queue strategies

Ensure idempotent writes to TSDB

Build DB ingestion adapters

Build API ingestion adapters

Build SFTP ingestion adapters

Implement dynamic configuration management

Write production-grade code

Optimize code performance

Work in cloud-native environment

Collaborate with cross-functional teams

How You'll Work.

Team & Collaboration

Cross-functional teams; Globally distributed team; Across cultures; Across organizations; Across time zones

Communication Scope

Articulate technical decisions

Process & Methodology

Agile

Full Job Description

ABOUT THE ROLE SourceFuse is looking for a Senior Go Backend Engineer to join the team building the execution layer of a telecom-grade 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) Key Responsibilities - Build high-performance Kafka consumers and producers in Go for a telecom-grade 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 per

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