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Company Description NCS is a leading AI Tech Services company. With a 15,000-strong team across the Asia Pacific, NCS scales its platforms and capabilities to provide clients with greater agility and AI expertise…
Build and maintain scalable data pipelines, integrate diverse data sources, and ensure high-quality data processing for analytics and ML using tools like Talend, PySpark, and SQL.
Build and maintain scalable data pipelines on Databricks and Azure, integrating diverse sources and ensuring clean, reliable data for analytics and ML workloads.
Design and maintain scalable data pipelines on Databricks and Azure, integrating diverse sources to support analytics and ML workloads while collaborating with cross-functional teams.
Build and maintain scalable ETL pipelines using Talend, PySpark, and SQL to integrate data sources for analytics and ML workloads.
Develop, enhance, and maintain enterprise Java applications for a client-focused outsourcing team in Singapore.
Designs and maintains on-premises Kubernetes clusters, deploys containerized apps, and collaborates with dev/ops teams to ensure smooth infrastructure operations.
Designs, deploys, and secures on-premises Kubernetes clusters and containerized apps using Docker, Helm, and Terraform, while integrating Kafka and monitoring stacks like Prometheus/Grafana.
Build full-stack web apps and integrate AI features using modern stacks, AI coding assistants, and LLM APIs to deliver enterprise solutions.
Lead a team to design and build cloud-based data pipelines using Spark, Kafka, Airflow, and DBT for analytics across APAC.
Designs and builds scalable data infrastructure and ETL pipelines using Python, Java, SQL, and cloud tools to support analytics and ML.
Designs and enforces data governance policies to maintain high-quality master data and ISO compliance in a regulated environment.
Builds and maintains scalable data pipelines and infrastructure using Python, SQL, and cloud services to support analytics and machine learning workflows.
Designs and maintains scalable data pipelines and storage systems using Python, Java, Spark, and SQL/NoSQL databases to ensure data quality and deliver business insights.
Builds and maintains automated data pipelines using Spark, Kafka, Airflow, and cloud platforms like Azure or AWS to integrate and process large-scale data for AI-driven analytics.
Designs and maintains data pipelines and warehouses, transforming raw data into insights using Oracle, PySpark, and Azure SQL for AI-driven analytics.
Designs and enforces data governance policies, manages master data, and ensures compliance with standards for secure, high-quality data across teams.
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