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Build and maintain scalable data pipelines and AI/ML platforms using AWS, Snowflake, and Databricks to support analytics and model delivery.
Design and build data pipelines, warehouses, and lakes for enterprise clients, using SQL, Python, and cloud platforms like Snowflake.
Build and maintain ML infrastructure for credit-risk systems, deploying models, optimizing pipelines, and improving data quality and observability.
Teach data engineering, cloud, and analytics modules at a polytechnic while designing curriculum and guiding student projects using Python, Spark, and cloud platforms.
Build and maintain cloud-native data pipelines and lakehouse systems using Spark, PySpark, Iceberg, and streaming tools to modernize OCBC’s financial data infrastructure.
Build and maintain ETL/ELT pipelines and data transformations to turn raw logs and usage data into reliable analytics for a speech-intelligence startup in Singapore.
Design and build cloud-based data analytics infrastructure using AWS, Databricks, and IDMC, migrating and modernizing healthcare data pipelines and ETL workflows.
Design and maintain data pipelines and integrations for a fast-growing beauty ecommerce portfolio, translating business needs into scalable data solutions to support decision-making.
Build and maintain ETL pipelines and data warehouses for a high-frequency trading firm, integrating global equity datasets and ensuring data accuracy for trading and research.
Build and maintain scalable data pipelines and infrastructure to power analytics and machine learning at a Southeast Asian AI venture.
Design and maintain scalable AWS data pipelines using PySpark, AWS Glue, and Lambda to enable analytics and business intelligence.
Build and maintain cloud-native data pipelines and dimensional models on Snowflake and AWS, using SQL, Stored Procedures, and Snowpipe to ingest and transform enterprise data.
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 maintain scalable data pipelines using PySpark, AWS Glue, and Step Functions, while automating infrastructure with Terraform and CI/CD.
Design and maintain scalable data pipelines, ETL/ELT processes, and data warehouses to support analytics and BI applications.
Designs and maintains cloud-based data pipelines and warehouses using AWS, Databricks, and Informatica to support healthcare analytics and reporting.
Builds scalable data pipelines and backend services using Java, SQL, and Scala to power analytics and reporting for a fintech company.
Build and maintain scalable data pipelines on Databricks using PySpark, refactor legacy ETL to modern ELT, and ensure data quality and reliability for analytics.
Design and maintain scalable data pipelines and warehouses to power analytics and ML, using SQL, Python/Java, and tools like Spark and Presto.
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