
Senior Data Protection Platform Engineer
- Kuala Lumpur
- Permanent
- Full-time
- Drive the development of enterprise technology architecture, platform engineering standards, and security frameworks for our core data platform.
- Implement comprehensive security controls across our unified data environment, ensuring alignment with industry and regulatory compliance standards.
- Promote operational excellence by supporting system performance, scalability, and reliability.
- Contribute to platform modernization efforts, integrating legacy and modern systems across the enterprise.
- Design and implement automated security monitoring, vulnerability scanning, and identity and access management solutions.
- Leverage DevOps practices, CI/CD pipelines, and Infrastructure-as-Code (IaC) tools to streamline deployments and enhance platform consistency.
- Support disaster recovery and high-availability strategies for critical enterprise platforms.
- Collaborate with engineering and operations teams to deliver business-aligned platform solutions.
- Provide strategic input on platform investments, security risks, and infrastructure improvements.
- Partner with senior engineers to build long-term technical roadmaps focused on reducing operational complexity and increasing scale.
- Bachelor’s degree in Technology, Engineering, Computer Science, or a related technical field.
- proven experience in enterprise technology, platform operations, or security engineering.
- Hands-on experience with CI/CD pipelines, DevOps principles, and Infrastructure-as-Code (e.g., AWS CDK, Azure Bicep).
- Familiarity with ITIL frameworks, Agile methodologies, and enterprise governance standards.
- Strong technical foundation in big data tools such as Apache Spark, Hadoop, Kafka, and Flink.
- Experience working with major cloud platforms (AWS, GCP, Azure) and cloud-native data services (e.g., BigQuery, Redshift, Snowflake, Databricks).
- Proficiency in SQL and one or more programming languages such as Python or Scala.
- Solid understanding of data warehousing, data modeling, and distributed systems architecture.
- Experience with Microsoft Azure, AWS, Databricks, and Palantir platforms.
- Knowledge of data ingestion pipelines, data governance, access control, and visualization tools.
- Proven ability to support large-scale, multi-cloud data platforms with a focus on cost-efficiency, performance, and resilience.
- Familiarity with performance tuning, distributed query optimization, and data indexing.
- Exposure to both real-time and batch processing pipelines and architectures.
- Demonstrated experience working in globally distributed, highly regulated environments with a focus on compliance, security, and risk management.
- Expertise in AI/ML-driven data engineering and applying intelligent automation to optimize platform workflows.