Big Data Platform Engineer - Geylang

Job Description

We are seeking a passionate Big Data Platform engineer to join our Global Data Platform team.

• Operating Global Data Platform components (VM Servers, Kubernetes, Kafka) and applications (Apache stack, Collibra, Dataiku and similar).
• Implement automation of infrastructure, security components, and Continuous Integration & Continuous Delivery for optimal execution of data pipelines (ELT/ETL).
• Develop solutions to build resiliency in data pipelines with platform health checks, monitoring, and alerting mechanisms, quality, timeliness, recency, and accuracy of data delivery are improved
• Apply DevSecOps & Agile approaches to deliver the holistic and integrated solution in iterative increments.
• Liaison and collaborate with enterprise security, digital engineering, and cloud operations to gain consensus on architecture solution frameworks.
• Review system issues, incidents, and alerts to identify root causes and continuously implement features to improve platform performance.
• Be current on the latest industry developments and technology trends to effectively lead and design new features/capabilities.

• Bachelor’s degree in Engineering/Information Technology/Computer Science, or related discipline
• 5-7 years of experience in building or designing large-scale, fault-tolerant, distributed systems, (for example: data lakes, delta lakes, data meshes, data lake houses, data platforms, data streaming solutions…)
• In-depth knowledge and experience in one or more large scale distributed technologies including but not limited to: Hadoop ecosystem, Kafka, Kubernetes, Spark
• Migration experience of storage technologies (e.g. HDFS to S3 Object Storage)
• Integration of streaming and file based data ingestion / consumption (Kafka, Control M, AWA)
• Experience in DevOps, data pipeline development, and automation using Jenkins and Octopus (optional: Ansible, Chef, XL Release, and XL Deploy)
• Expert in Python and Java or another static language like Scala/R, Linux/Unix scripting, Jinja templates, puppet scripts, firewall config rules setup
• VM setup and scaling (pods), K8S scaling, managing Docker with Harbor, pushing Images through CI/CD
• Experience using data formats such as Apache Parquet, ORC or Avro Experience in machine learning algorithms is a plus.
• Hands-on experience in integrating Data Science Workbench platforms (e.g. Dataiku)
• Cloud migration experience might come handy • Experience of agile project management and methods (e.g., Scrum, SAFe)
• Knowledge of financial sector and its products is beneficial

• Exceptional communication skills to interact with both technical teams and business stakeholders.
• Detail-oriented mindset with the ability to manage multiples tasks and prioritize effectively
• Proactive, collaborative, and customer-focused approach to solving problems and driving adoption
• Passion for enabling a data-driven culture and empowering users thought data solutions.

EA Number: 11C4879