Job description

[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]

• 3–5 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.