Senior Data Platform Engineer

Role Summary :

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.

This role will be responsible for ensuring Dataiku is stable, scalable, secure, and production-ready, while enabling data scientists to deploy, monitor, and operate machine learning models efficiently.

The ideal candidate combines Dataiku administration expertise, Linux & cloud fundamentals, and hands-on ModelOps/MLOps experience across CI/CD, monitoring, and automation.

Key Responsibilities :

Dataiku Platform Administration :

- 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.

ModelOps / MLOps Enablement :

- 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.

Cloud, Infrastructure & Automation :

- 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.

Collaboration & Support :

- 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.

Required 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 :

1. Linux system administration.

2. Python scripting.

3. CI/CD pipelines and Git-based workflows.

4. Cloud platforms (Azure, AWS, or GCP).

- Hands-on experience in implementing ModelOps / MLOps concepts, including model deployment and monitoring.

- Familiarity with Kubernetes and containerized workloads.

- Strong troubleshooting, analytical, and problem-solving skills.

Preferred / Nice-to-Have Skills :

- Dataiku certifications (Core Designer, Advanced Designer, ML Practitioner).

- Experience supporting enterprise-scale ML platforms.

- Knowledge of monitoring and observability tools (Grafana, Prometheus).

- Exposure to IaC tools such as Terraform or Ansible.

- Experience transitioning platforms from vendor-managed to in-house support.

What Success Looks Like in This Role :

- 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.

Skills

Dataiku, System Administration, Monitoring Tools, CI/CD, MLOps, Linux, DataOps, Cloud Infrastructure, IT Infrastructure Automation, DevOps, Python