Job Title: Big Data Platform Engineer

Location: Singapore

Team: Global Data Platform

We are looking for a passionate and experienced Big Data Platform Engineer to join our dynamic Global Data Platform team. This role offers the opportunity to work on cutting-edge technologies and contribute to building and operating resilient, scalable, and secure data platforms.

Key Responsibilities:

• Manage and operate core Global Data Platform components such as VM Servers, Kubernetes, Kafka, and applications within the Apache stack, including Collibra, Dataiku, and similar tools.
• Automate infrastructure and security components, and implement CI/CD pipelines to ensure seamless and efficient execution of ELT/ETL data pipelines.
• Enhance data pipeline resilience through monitoring, alerting, and health checks, ensuring high standards of data quality, timeliness, and accuracy.
• Apply DevSecOps principles and Agile methodologies to deliver robust and integrated platform solutions incrementally.
• Collaborate with enterprise security, digital engineering, and cloud operations teams to define and agree on architectural solution frameworks.
• Investigate system issues and incidents, identify root causes, and implement continuous improvements to optimize platform performance.
• Stay up to date with emerging technologies and industry trends to drive innovation and new feature development.

Required Skills and Experience:

• Bachelor’s degree in Engineering, Computer Science, Information Technology, or a related field.
• 5–7 years of experience designing or building large-scale, fault-tolerant distributed systems (e.g., data lakes, data meshes, streaming data platforms).
• Strong hands-on expertise with distributed technologies like Kafka, Kubernetes, Spark, and the broader Hadoop ecosystem.
• Experience in storage migration (e.g., from HDFS to S3 or similar object storage).
• Proficient in integrating streaming and batch ingestion pipelines using tools like Kafka, Control-M, or AWA.
• Demonstrated experience with DevOps and automation tools such as Jenkins, Octopus, and optionally Ansible, Chef, XL Release, XL Deploy.
• Strong programming skills in Python and Java (or other languages like Scala, R), along with Linux/Unix scripting and automation using Jinja, Puppet, and firewall configuration.
• Experience with Kubernetes pod scaling, Docker image management via Harbor, and CI/CD deployment of containers.
• Familiarity with data serialization formats such as Parquet, ORC, or Avro.
• Exposure to machine learning and Data Science platforms like Dataiku is a plus.
• Cloud migration experience is advantageous.
• Comfortable working in Agile environments (e.g., Scrum, SAFe).
• Knowledge of the financial services industry and its products is a strong asset.

Soft Skills:

• Excellent communication skills with the ability to collaborate across technical and business teams.
• Detail-oriented and highly organized, with strong prioritization and multitasking abilities.
• Proactive, customer-focused, and collaborative approach to problem-solving and project execution.
• A strong advocate for data-driven culture and the democratization of data across the organization.