Data Engineer

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