About the job
At Dev. Pro, we are dedicated to projects that impact millions globally, and we recognize that it’s the talented individuals behind the technology who drive our success. We pride ourselves on fostering an inclusive, friendly, and supportive workplace.
About This Opportunity
We are seeking a skilled DevOps Engineer to enhance our remote engineering team. The successful candidate will be instrumental in deploying, monitoring, and optimizing cloud platforms utilized by our data scientists. This position demands hands-on experience in cloud infrastructure, modern DevOps methodologies, secure data operations, and automation frameworks. Collaboration with data scientists, machine learning engineers, and data engineers will be essential to ensure our analytics systems operate securely, efficiently, and at scale. You will work alongside our Platform Engineering team to define and implement best practices that can be standardized and reused across our organization.
Key Responsibilities
- Cloud Infrastructure & Operations: Oversee, scale, and optimize cloud environments for data science workloads, primarily using AWS, Databricks, and dbt. Provision, maintain, and optimize compute clusters for ML workloads (e.g., Kubernetes, ECS/EKS, Databricks, SageMaker). Implement high-availability solutions for critical analytics platforms, showcasing deep expertise in AWS resource management and provisioning, including IAM roles and permissions.
- DevOps & Automation: Create CI/CD pipelines for model deployment, infrastructure-as-code (IaC), and automated testing utilizing industry-standard toolchains. Develop monitoring, alerting, and logging systems for cloud and ML infrastructure (e.g., Datadog, CloudWatch, Prometheus, Grafana, ELK). Automate provisioning, configuration, and deployments using tools such as Terraform, CloudFormation, and GitHub Actions.
- Data Platform Support: Enhance data ingestion, transformation, and model execution workflows through platform capabilities and automation. Build and maintain self-service capabilities for data scientists to provision and manage reliable, reproducible environments for research and development. Collaborate with Data Engineering to sustain integrations between data pipelines and cloud systems. Share responsibilities for provisioning and operating application networking capabilities that support data platforms, including API gateways, CDNs, application load balancers, TLS, and WAFs.
- Security, Compliance & Governance: Establish and operationalize security and compliance controls for data science platforms in alignment with enterprise cloud standards. Conduct periodic risk assessments, best practice reviews, and remediation efforts.
