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Designs and optimizes cloud-based data pipelines and warehouses using Spark/PySpark, SQL, and real-time processing to support analytics and data science teams.
Design and maintain scalable data pipelines, ETL/ELT processes, and cloud-based data warehouses using Spark, SQL, and cloud platforms like AWS/Azure/GCP.
Designs and builds data pipelines, warehouses, and reporting systems using Python, PySpark, Hive, and cloud platforms to support analytics and visualization tools like Tableau.
Lead data engineering projects to build and maintain investment data platforms using Python, PySpark, AWS, and Databricks, enabling analytics and AI-driven insights for a sovereign wealth fund.
Design and build scalable cloud-native data platforms for a major bank, using Lakehouse architectures, real-time streaming, and AWS to deliver analytics-ready datasets.
Leads a Python/PySpark data-engineering team building a trade-surveillance system and integrating GenAI tools to improve delivery quality and team productivity.
Build and maintain scalable data pipelines and GenAI applications for AI-driven analytics projects, collaborating with data scientists and engineers to deliver ML solutions for clients.
Build and maintain scalable data pipelines and ETL workflows on AWS using PySpark, Glue, Lambda, and Step Functions, while automating infrastructure with Terraform and CI/CD.
Build and maintain scalable data pipelines on Databricks and Azure, integrating diverse sources and enabling analytics and ML workloads with PySpark and Delta Lake.
Lead a team to modernize data platforms by migrating to AWS and building scalable pipelines with Databricks, Informatica IDMC, and Tableau.
Build and maintain scalable data pipelines on AWS using PySpark, Glue, Lambda, and Terraform, while automating deployments with CI/CD.
Designs and builds data pipelines and warehouses for a bank using Hadoop, Spark, and Teradata, enabling analytics and ML model development.
Build automated reports, dashboards, and AI-assisted workflows using SQL, Python/PySpark, and ETL tools for data-driven insights.
Lead a data engineering team to maintain cloud data pipelines, warehouses, and lakes, migrating legacy systems to Snowflake and AWS while ensuring stability and performance.
Build and maintain cloud-native data pipelines and lakehouse systems using Spark, PySpark, Iceberg, and streaming tools to modernize OCBC’s financial data infrastructure.
Designs and implements AI-powered data pipelines and reporting solutions using Python, PySpark, and ETL tools like Informatica, with dashboards in SAP BO/Tableau.
Build and maintain scalable data pipelines and infrastructure to power analytics and machine learning at a Southeast Asian AI venture.
Build and maintain scalable ETL/ELT pipelines using SQL and PySpark to feed AI and analytics systems in a cloud-based data platform.
Build and maintain ETL/ELT pipelines and PySpark jobs to feed AI and analytics platforms; write SQL, validate data, and troubleshoot issues in a cloud-based data stack.
Build and optimize big-data pipelines and analytics using Hadoop, PySpark, Scala, and Python to process large-scale datasets and integrate data from multiple sources.
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