Data Engineer

Company size: 51-250

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Job description

A U.S.-based company that is lowering the cost of AI data storage and access while protecting its privacy for enterprise is looking for a Data Engineer. The engineer will be in charge of creating infrastructure that analyzes and provides access to huge data. The company is improving the information's signal-to-noise ratio, making AI more widely available, more economical, and safer to employ. The company has managed to secure more than $44mn during their Series A round of funding. 


Job Responsibilities:

  • Design, deploy, and manage a robust data observability stack in AWS to ensure continuous data quality, reliability, and visibility
  • Implement and optimize tools such as Loki, Grafana, Tempo, and Mirmi to provide efficient logging, tracing, and monitoring solutions
  • Use Prometheus for effective system monitoring and alerting purposes
  • Employ ECS/Kubernetes orchestration for efficient container management
  • Develop, manage, and optimize Docker containers to support scalable and reliable data processes
  • Collaborate with other teams to understand data needs, ensuring the observability stack meets business requirements
  • Continuously research and stay updated with the latest technologies and best practices in data observability
  • Provide training and documentation to team members on observability tools and best practices

Job Requirements:

  • Minimum 4 years of professional experience in data observability or related fields
  • Proven experience in setting up and managing observability tools such as Loki, Grafana, Tempo, and Mirmi
  • Proficient knowledge of Prometheus for monitoring and alerting
  • Strong expertise in AWS infrastructure and services
  • Hands-on experience with ECS and Kubernetes for container orchestration
  • Deep understanding of Docker containerization and its best practices
  • Strong problem-solving skills, with an analytical mindset
  • Excellent communication skills, both written and verbal

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