Senior Backend Engineer (Go / AWS Streaming)

New
C
Creative ChaosAI orchestration
Workable workplace: remote; Workable locations: Pakistan. India. Germany. Romania. Argentina. BrazilFull-TimeSenior
Salary not disclosed
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Job Details

Languages
Plain English
Experience
5+ years of backend engineering experience, with at least 2–3 years writing production Go.
Required Skills
AWSDockerSQLApache KafkaGoTerraform

Requirements

  • Have 5+ years of backend engineering experience.
  • Have at least 2–3 years of experience writing production Go.
  • Understand Go goroutines, channels, and concurrency patterns under load.
  • Have built and operated production streaming data pipelines with AWS Kinesis or a comparable system such as Kafka.
  • Understand ordering, partitioning, exactly-once and at-least-once delivery, and replay.
  • Have experience with AWS IoT Core or another device-telemetry ingestion platform, including MQTT, device authentication, and high-fan-in workloads.
  • Have designed and optimized Amazon Redshift or a comparable warehouse such as Snowflake or BigQuery for production analytics.
  • Write strong SQL and know how to optimize slow queries.
  • Have strong AWS skills, including Lambda, S3, IAM, and CloudWatch.
  • Be comfortable with infrastructure as code such as Terraform or CDK, Docker, and CI/CD.
  • Be able to explain architecture trade-offs to a US product team in plain English and write design documents.

Responsibilities

  • Design, build, and maintain production Go services and APIs.
  • Build device-to-cloud ingestion using AWS IoT Core, MQTT, device authentication, message routing, and downstream rules.
  • Design and operate Kinesis Data Streams and Firehose pipelines, including partitioning, consumers, retries, back-pressure, and dead-letter handling.
  • Design Redshift schemas, distribution and sort keys, and data-loading patterns for analytics.
  • Ensure warehouse data is correct, complete, and ready for analytics.
  • Build monitoring, alerting, and dashboards for the pipeline.
  • Track latency, data loss, and AWS spend, and improve cost per million events.
  • Lead design discussions, review code, write technical documents, and mentor engineers.
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