Data Platform Engineer

Cerebras SystemsSunnyvale, CA
6h$160,000 - $250,000

About The Position

As a Platform Engineer on the Cerebras Data Analytics team, you will design, build, and maintain a reliable, high-performance cloud data platform that enables the company’s success via data-driven insights. Your work will amplify the impact of data engineers and data scientists to address diverse needs across hardware, software, operations, and business intelligence. The ideal candidate is a proactive, independent problem solver who takes pride in delivering efficient and effective solutions.

Requirements

  • 3+ years of professional experience in platform engineering, reliability engineering, DevOps, or an infrastructure-focused role.
  • 3+ years of hands-on experience in AWS, especially EC2, S3, CloudWatch, and/or IAM.
  • Proficiency in at least one advanced programming language (e.g. Python, C++).
  • Experience with relational SQL databases (e.g. PostgreSQL, MySQL).
  • Experience with Infrastructure-as-Code platforms (e.g. Terraform, AWS CloudFormation).
  • Experience with Git.

Nice To Haves

  • Strong proficiency in Python.
  • Experience with data engineering, data analytics, and/or business intelligence.
  • Experience with containerization tools and platforms (e.g. Docker, Kubernetes).
  • Experience with monitoring/observability tools and platforms (e.g. Datadog, Splunk, Prometheus, Loki, Grafana).
  • Experience with front-end technologies and frameworks (e.g. HTML, JavaScript).
  • Experience with networking and cybersecurity.

Responsibilities

  • Design, deploy, and maintain core infrastructure in AWS for data storage, processing, and reporting.
  • Maintain and scale databases and data lakes that store ever-increasing volumes of data.
  • Create tools, automations, and frameworks to improve developer efficiency.
  • Create monitoring and alerting systems to effectively identify risks and quickly resolve issues.
  • Continuously improve the reliability, scalability, and cost-effectiveness of the entire data platform.
  • Collaborate cross-functionally with IT, Security, and engineering teams to securely integrate data sources and infrastructure in various locations.
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