Overview

We are seeking a Senior Platform Engineer to own and evolve our Dataiku Data Science Platform, with strong focus on platform administration, reliability, security, and ModelOps.

Responsibilities

• Own end-to-end administration of Dataiku DSS environments (installation, upgrades, patching, backups, restores).
• Manage hub-and-spoke or multi-instance Dataiku architectures.
• Troubleshoot and resolve performance, infrastructure, and platform stability issues.
• Apply security best practices including user access control, secrets management, and vulnerability remediation.
• Plan and execute capacity management, scaling, and disaster recovery strategies as needed.
• Design and support model deployment pipelines using Dataiku automation, APIs, and CI/CD tools.
• Enable model versioning, promotion, rollback, and lifecycle management across environments.
• Implement model monitoring (performance drift, data drift, operational health).
• Partner with data scientists to productionize ML workflows using best-practice ModelOps patterns.
• Define and document standard operating procedures (SOPs) for model deployment and operations.
• Administer Dataiku on Linux-based environments across cloud platforms.
• Work with containers and Kubernetes for scalable and resilient deployments.
• Build automation using Python, Bash, Ansible, or Terraform to reduce manual operations.
• Integrate Dataiku with enterprise tools such as Git, CI/CD pipelines, monitoring (Grafana/Prometheus), and ServiceNow.
• Administer and support Dataiku integrations with enterprise databases - Preferably Snowflake.
• Troubleshoot query performance, concurrency, and cost-related issues arising from Dataiku workloads on Snowflake.
• Act as the primary platform contact for Dataiku.
• Provide support and participate in incident response and root-cause analysis.
• Mentor junior engineers to enable L1/L2 support and contribute to internal platform standards.
• Work closely with vendors during transition phases and drive in-house ownership of the platform.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field (16 years of formal education).
• 7+ years of experience in platform engineering, data platform administration, or DevOps.
• 3+ years of hands-on Dataiku administration experience.
• Strong experience with:
• Linux system administration
• Python scripting
• CI/CD pipelines and Git-based workflows
• Cloud platforms (Azure, AWS, or GCP)
• Handson experience in implementing ModelOps / MLOps concepts, including model deployment and monitoring.
• Familiarity with Kubernetes and containerized workloads.
• Strong troubleshooting, analytical, and problem-solving skills.
• Dataiku certifications (Core Designer, Advanced Designer, ML Practitioner).
• Knowledge of monitoring and observability tools (Grafana, Prometheus).
• Exposure to IaC tools such as Terraform or Ansible.
• Dataiku platform runs stably, securely, and cost-effectively with minimal external dependency.
• ML models move from development to production faster and more reliably.
• Clear ModelOps standards and automation are in place.
• Data scientists spend more time on modeling, less time on platform issues.