Databricks MLOps Platform Manager | Hybrid Global Role

BSI; Kuala Lumpur; Hybrid; MYR 495,000 - 770,000; Full time

Benefits offered by this job

27 days annual leave

Health insurance

Pension plan

Life insurance

Job summary

BSI is seeking a Databricks Platform Manager - ML Ops to lead the reliable operation of the Databricks Lakehouse Platform and ML workflows. The role is permanent and hybrid, with responsibilities spanning incident management, governance, and cost optimization across global teams including the UK and Kuala Lumpur.

You will collaborate with data engineering and data science, implement CI/CD for ML models, and drive platform standards while balancing risk and innovation.

Qualifications

• Proven experience managing data/analytics platforms and MLOps in large enterprises.
• Hands-on with Databricks including workspace, clusters, Delta Lake, Unity Catalog.
• Experience implementing MLOps across model lifecycle (CI/CD, versioning, monitoring).
• Strong stakeholder management and alignment of platform priorities with business goals.
• Experience working with security, risk and governance teams to evidence controls.
• Experience managing suppliers and delivery partners.

Responsibilities

• Own and operate the Databricks Lakehouse Platform and MLOps services.
• Lead incident, change, and request processes across the platform.
• Develop standardized MLOps frameworks and tooling.
• Collaborate with Data Engineering and Data Science to operationalize ML models.
• Ensure security, compliance, and governance controls.
• Own platform roadmap, standards, and cost optimization.
• Manage vendor and supplier relationships and performance.
• Provide guidance, training, and enablement to teams.

Skills

Platform management

MLOps

Databricks

CI/CD

Governance

Stakeholder management

Tools

Delta Lake

Unity Catalog

Access controls

Job description

BSI is seeking a Databricks Platform Manager - ML Ops to lead the reliable operation of the Databricks Lakehouse Platform and ML workflows. The role is permanent and hybrid, with responsibilities spanning incident management, governance, and cost optimization across global teams including the UK and Kuala Lumpur.

You will collaborate with data engineering and data science, implement CI/CD for ML models, and drive platform standards while balancing risk and innovation.