
Senior Data Platform Services Engineer
- Kuala Lumpur
- Permanent
- Full-time
- Drive contributions to enterprise technology architecture, security frameworks, and platform engineering for our core data platform.
- Lead end-to-end security implementation, ensuring compliance with industry standards and regulatory requirements across our unified data platform.
- Promote operational excellence by enhancing system performance, availability, and scalability.
- Support modernization and transformation initiatives, facilitating integration with enterprise IT systems.
- Design and implement automated security monitoring, vulnerability assessments, and identity management solutions.
- Apply DevOps principles, CI/CD pipelines, and Infrastructure-as-Code (IaC) to improve deployment efficiency and platform consistency.
- Support disaster recovery planning and ensure high availability of enterprise platforms.
- Collaborate with engineering and operations teams to align platform solutions with business goals.
- Provide strategic guidance on platform investments, security risks, and operational improvements.
- Work alongside senior engineers to develop long-term technical roadmaps that reduce operational overhead and enhance scalability.
- Bachelor’s degree or equivalent experience in Technology, Engineering, or a related technical field.
- 3–5 years’ experience in enterprise technology, security, or platform operations within large-scale environments.
- Hands-on experience with CI/CD pipelines, DevOps methodologies, and Infrastructure-as-Code tools (e.g., AWS CDK, Azure Bicep).
- Familiarity with ITIL, Agile delivery frameworks, and enterprise governance models.
- Proficiency in big data technologies such as Apache Spark, Hadoop, Kafka, and Flink.
- Experience with cloud platforms including AWS, GCP, Azure, and cloud-native data solutions like BigQuery, Redshift, Snowflake, and Databricks.
- Strong skills in SQL, Python, or Scala, with practical experience in data platform engineering.
- Solid understanding of data modeling, data warehousing, and distributed systems architecture.
- Expertise with Microsoft Azure, AWS, Databricks, and Palantir platforms.
- Knowledge of data ingestion pipelines, governance frameworks, security best practices, and data visualization tools.
- Experience managing multi-cloud data platforms at scale, balancing cost, performance, and resilience.
- Familiarity with performance tuning, data indexing, and optimizing distributed query execution.
- Exposure to real-time and batch data streaming architectures.
- Proven track record in navigating highly regulated, global environments while ensuring compliance, security, and enterprise-wide risk management.
- Experience applying AI/ML techniques to data engineering workflows, leveraging intelligent automation to boost efficiency.