
Senior Data Platform Services Engineer
- Kuala Lumpur
- Permanent
- Full-time
- Design and implement scalable platform architecture and security frameworks for bp’s core data platforms.
- Drive end-to-end security implementation to meet regulatory and industry compliance standards.
- Support system performance, availability, and scalability as part of operational excellence.
- Lead modernization and integration initiatives with enterprise IT systems.
- Develop automated security monitoring tools, perform vulnerability assessments, and support identity management solutions.
- Apply DevOps, CI/CD, and Infrastructure-as-Code (IaC) practices to streamline deployment and improve platform reliability.
- Support disaster recovery strategies and high availability across enterprise platforms.
- Collaborate with engineering and operations teams to deliver solutions that align with business needs.
- Advise on platform investments, manage security risks, and recommend operational improvements.
- Partner with senior engineers to shape technical roadmaps and reduce long-term operational complexity.
- Bachelor’s degree or equivalent experience in Technology, Engineering, or a related field.
- proven experience in enterprise technology, security, or platform operations.
- Hands-on experience with CI/CD pipelines, DevOps practices, and IaC tools like AWS CDK or Azure Bicep.
- Strong understanding of ITIL, Agile delivery, and enterprise governance.
- Proficiency in big data tools such as Apache Spark, Hadoop, Kafka, and Flink.
- Experience with cloud platforms (AWS, GCP, Azure) and data solutions like BigQuery, Redshift, Snowflake, and Databricks.
- Skilled in SQL, Python, or Scala, with practical experience in data platform engineering.
- Knowledge of data modeling, data warehousing, and distributed systems.
- Technical expertise in Microsoft Azure, AWS, Databricks, and Palantir.
- Understanding of data ingestion, governance, and security best practices.
- Experience managing multi-cloud data platforms with a focus on cost, performance, and resilience.
- Familiarity with data indexing, performance tuning, and distributed query optimization.
- Experience with both real-time and batch data streaming architectures.
- Proven success in regulated, enterprise environments—navigating security, compliance, and risk.
- Experience applying AI/ML to automate and optimize data engineering workflows.