[What the role is]
To design, build, secure, and operate the Enterprise Data & AI platform, ensuring it is reliable, cost-efficient, and compliant with enterprise governance standards. This role owns both the technical platform layer (clusters, jobs, CI/CD, monitoring) and the security layer (encryption, IAM, audit).
This is a 2-year contract position with the Digital Services & Technology Office.
[What you will be working on]
Platform Operations
- Configure and maintain Enterprise Data and AI platform (e.g. Databricks workspaces, clusters, SQL warehouses, endpoints and workflows).
- Automate provisioning and deployments using Terraform, Databricks CLI, or APIs.
- Design and govern CI/CD frameworks used by Data Engineers for ETL/ML deployments, ensuring secure, compliant, and automated delivery workflows.
- Monitor platform usage, cost trends, and optimize performance of workloads.
- Maintain platform reliability and meet defined uptime and service-level objectives.
Security Engineering
- Implement and maintain security controls for the enterprise data platform, including encryption, secrets management, and secure access patterns.
- Define and enforce role-based and attribute-based access policies across data assets and cloud compute resources.
- Configure secret scopes and secure service principal access.
- Monitor platform audit and activity logs to detect policy violations, anomalous access, and compliance risks.
- Ensure platform operations align with NP's security, compliance, and regulatory requirements (e.g., IM8, NIST, GDPR. PDPA where applicable).
Collaboration
- Work closely with Data Engineers, Governance Leads, and Analysts to ensure data pipelines, workflows, and products adhere to security and platform standards.
- Work closely with CI/CD team to integrate monitoring and alerting into observability stack.
- Advise leadership on platform performance and security posture and risks, optimisation opportunities, as well as compliance gaps.
[What we are looking for]
- 35 years in cloud platform engineering or security engineering.
- Proven experience managing and securing large-scale data or ML platforms.
- Prior work in regulated industries (finance, healthcare, government) is a plus.
Skills & Certifications
- Certifications:
- Degree or Diploma in Computer Science, Computer Engineering, Information Technology or equivalent.
- Cloud security certs: Azure Security Engineer Associate / AWS Security Specialty / GCP Security Engineer.
- Infrastructure-as-code: Terraform or equivalent.
- Databricks Certified Administrator or Databricks Security Engineer is a plus
- Technical Skills:
- Cloud IAM, KMS, VPC/VNet, firewall/security groups.
- Encryption standards (AES, envelope encryption).
- CI/CD (Azure DevOps, GitHub Actions, Jenkins).
- Databricks platform administration (clusters, jobs, SQL warehouses, UC integration).
- Other Skills:
- Strong knowledge of monitoring/observability stacks (e.g. Azure Monitor).
- Incident response and audit log analysis.
- Experience in GCC/GCC2.0 is a plus.
Attributes
- Reliability-focused and security-first mindset with attention to detail.
- Strong collaborator with engineering, governance, and leadership.
- Proactive in risk identification and mitigation.
- Balanced approach: performance and cost optimization while ensuring compliance.
