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DevOps / Data Engineer

DevOps / Data Engineer

Pivotal Solutions IncFargo, ND, United States
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Job Description

  • Drive the infrastructure strategy alongside the rest of the DevOps team
  • Be responsible for building, managing, and automating our AWS infrastructure
  • Oversee the maintenance and growth of our data lakehouse infrastructure and implementation
  • Champion security by adopting necessary tools and processes
  • Provide leadership to the entire engineering team on various infrastructure and big data topics
  • Identify and adopt high-level technologies, processes, and services that impact the organization on a system-wide scope
  • Participate in the L2 rotation for engineering support

Requirements

  • 8+ years of experience as a DevOps Engineer
  • 5+ years of experience with the AWS cloud platform, including proficiency with AWS SDK, AWS CLI / UI, and services such as VPC, Route53, Private and Public subnets, route tables, IGW, EC2 Instances, CloudFront, API Gateway, IAM, ELB, Autoscaling, CloudWatch, EFS, NFS, EBS, S3, RDS, Lambda, SQS / SNS, Kafka, Security groups, etc.
  • 5+ years of experience with Terraform / Terragrunt
  • 5+ years of experience with event processing infrastructure
  • 2+ years of experience as a Data Engineer with Databricks, including data pipelines, Debezium, Spark, and data modeling
  • Expert proficiency with Python
  • Model serving experience
  • Expert proficiency in deploying, maintaining, and scaling applications
  • Proficiency with Docker, Kubernetes, and Serverless functions
  • Expert proficiency in setting up CI / CD pipelines (tools / processes / governance)
  • Experience creating and maintaining fully automated CI / CD pipelines for code deployment using tools such as Git, CircleCI, AWS Code build, and Code Deploy / Code pipeline
  • Proficient with both Relational and Non-Relational databases
  • Experience with Security vulnerability scanning tools (Guard Duty, Inspector)
  • Experience building Monitoring dashboards and leveraging tools such as Cloudwatch, Datadog, and Sumologic
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