Develop scalable real-time machine learning and data systems using Hadoop ecosystem technologies. Build batch and streaming ingestion and transformation frameworks for multimodal data, deploy models through Cloudera Machine Learning, create internal full-stack tools, and optimize application performance and resource utilization.
- Experience working with ML platforms such as CML, Spark
MLlib, and Python ML libraries (scikit‑learn, XGBoost), including model
deployment.
- Design and develop highly scalable, Real time systems
using Hadoop ecosystem components(Iceberg, Spark, Ozone, Trino, Hive,
Ranger, Kafka, Flink and Nifi)
- Build robust data ingestion and transformation
frameworks using Java, Spark, Python, and shell scripting for ingesting
multi model data(image, audio, video, unstructured documents) with both
batch and real-time.
- Develop full‑stack applications and internal
engineering tools using Python, shell scripting, and modern web frameworks
(e.g., Flask, React).
- Collaborate closely with data scientists to
operationalize machine learning models using Cloudera Machine Learning
(CML).
- Perform performance tuning and optimization of data
applications on Hadoop to ensure optimal resource utilization.
Technopals Pte.Ltd. Singapore, Singapore, SGP Office
Singapore, Singapore
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What you need to know about the Singapore Tech Scene
The digital revolution has driven a constant demand for tech professionals across industries like software development, data analytics and cybersecurity. In Singapore, one of the largest cities in Southeast Asia, the demand for tech talent is so high that the government continues to invest millions into programs designed to develop a talent pipeline directly from universities while also scaling efforts in pre-employment training and mid-career upskilling to expand and elevate its workforce.
