I49 - Data Engineer - Platform (107)

About the Role

We are seeking a highly motivated Data Platform Engineer to join our Data Engineering team in Singapore. The team is responsible for the design, operation, and evolution of the Enterprise Data Lake and Data Platform that supports thousands of users across cloud and on-premises environments. In this role, you will design, build, maintain, and optimize scalable, secure, and reliable data platforms that enable analytics, reporting, machine learning, enterprise search, and AI-driven solutions.

Key Responsibilities

• Design, develop, and implement scalable data and platform solutions across AWS and hybrid/on-premises environments.

• Build and maintain robust data pipelines, platform services, and automation frameworks using Python, PySpark, SQL, and cloud-native technologies.

• Support and enhance enterprise capabilities including data lakes, metadata management, search platforms, and AI services.

• Develop and maintain CI/CD pipelines, automated testing frameworks, and deployment processes.

• Implement, integrate, and support technologies such as OpenSearch, Bedrock, AgentCore, MCP, and related platform services.

• Monitor and improve platform reliability, security, performance, observability, and cost efficiency.

• Troubleshoot and resolve production issues while ensuring platform stability and operational excellence.

• Collaborate with cross-functional teams to drive platform modernization and continuous improvement initiatives.

Mandatory Requirements

• 3-5+ years of hands-on experience building and supporting production-grade data pipelines using SQL, Python, and cloud technologies.

• Hands-on experience with AWS and/or hybrid cloud environments.

• Strong Linux/Unix administration and scripting experience with production support capabilities.

Detailed Requirements

• Data Engineering: Strong understanding of ETL/ELT processes, Data Lake/Lakehouse architectures, and distributed data processing frameworks.

• Cloud & Platform Engineering: Experience with AWS Glue, EMR, S3, Redshift, Lambda, Apache Spark, Airflow, DBT, Kafka/MSK, Apache Iceberg, OpenSearch, Hive, Trino, Presto, Bedrock, AgentCore and MCP.

• Platform Operations: Proficiency with Git, CI/CD pipelines, DevOps practices, Infrastructure as Code (IaC), and enterprise-scale platform support.

Preferred Qualifications

• Experience with Data Lake and Lakehouse platforms.

• Knowledge of streaming and event-driven architectures.