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We're looking for a DataOps Engineer to ensure the reliability, efficiency, and security of our data platform. You'll work at the intersection of DevOps and Data Engineering, automating processes and maintaining the infrastructure that supports our ML applications.
Tasks
Design and implement automated data infrastructure using IaC
Set up and maintain monitoring, alerting, and observability systems
Optimize platform costs and resource utilization
Implement and maintain CI/CD pipelines for data workflows
Enforce security best practices and compliance requirements
Troubleshoot platform issues and implement preventive measures
Manage pre/post processing workflows around ML models
Requirements
Required Qualifications:
Bachelor's or Master's in Computer Science, Engineering, or related field
3+ years experience in DevOps, Data Engineering, or similar role
Advanced Python/SQL programming skills
Proficiency with infrastructure-as-code (Terraform, CloudFormation)
Strong experience with containerization and orchestration (Docker, Kubernetes)
Knowledge of monitoring tools (Prometheus) and practices
Experience with Postgres Operator
Experience with Argon/Flux workflow engines
Understanding of security best practices and IAM
Strong experience with cloud platforms (AWS/GCP/Azure)
Experience with MLOps pipelines
Nice to Have:
Experience with data warehouses (Snowflake, BigQuery)