DevOps/Data Engineer
Pivotal Solutions
Salary undisclosed
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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
About this role
Pivotal Solutions is looking for a senior infrastructure leader who can own both the DevOps and data engineering sides of a growing operation. You'd be responsible for designing and automating AWS infrastructure at scale, managing a data lakehouse platform built on Databricks, and setting the technical direction for how the engineering team approaches infrastructure and big data challenges. This is a hands-on role that requires deep expertise across the full stack—from networking and containerization to CI/CD pipelines and event processing—but also the judgment to identify which new tools and approaches will move the needle for the organization.
The ideal candidate has at least eight years as a DevOps engineer with five-plus years specifically in AWS, Terraform, and event processing infrastructure. You'll also need solid data engineering chops, particularly with Databricks, Spark, and data pipelines. Beyond the technical depth, you should be comfortable mentoring the broader engineering team, participating in on-call rotations, and championing security practices. This is an in-office role in Fargo, North Dakota, suited for someone ready to take on strategic infrastructure work alongside hands-on engineering.
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Pay for this role
The employer didn't post a pay range for this role. That usually means pay is set in negotiation, which favors whoever arrives with numbers. Check ranges on comparable DevOps/Data Engineer postings in Fargo, and analyze any offer before you accept it.
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