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Designs and builds scalable AWS data pipelines using PySpark, AWS Glue, and serverless services to process and deliver data efficiently.
Design and build cloud-based data analytics infrastructure using AWS, Databricks, and IDMC, focusing on healthcare data pipelines and ETL/ELT workflows.
Lead a team to build and maintain scalable ETL pipelines and cloud data platforms for government projects using AWS services like S3, Glue, and Redshift.
Design and implement scalable cloud data architectures, lead Data Lakehouse development, and build ETL/ELT pipelines using Python, SQL, and Spark for a government-linked AI platform.
Build and maintain data pipelines and infrastructure for AI models that optimize Singapore’s transport network, ensuring high-quality, real-time data from sensors and systems is reliably ingested and governed.
Architect and maintain scalable data pipelines and warehouses (Snowflake, Redshift, Athena) to power analytics and AI workflows, using Python, SQL, Airflow, and Kafka.
Design and build scalable cloud-native data pipelines and lakehouse architectures for a government housing agency, using Python, Spark, Kafka, and AWS services.
Lead a cloud-based data engineering team to build and maintain robust data pipelines, migrate legacy systems to Snowflake and AWS Glue, and ensure high-quality data flows for analytics and reporting.
Designs and maintains cloud data infrastructure on AWS and Databricks, building ETL pipelines and optimizing storage/processing for analytics using Python/Java/Scala.
Build and optimize AWS-based data pipelines and Redshift warehouses for a government project, using Python, SQL, and DevOps practices to ensure secure, scalable data infrastructure.
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.
Job Description: Design, develop, optimize, and maintain data architecture and pipelines that adhere to ETL principles and business goals. Solve complex data problems to deliver insights that help the organization…
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.
Lead a team to modernize data platforms by migrating to AWS and building scalable pipelines with Databricks, Informatica IDMC, and Tableau.
Designs and builds cloud data pipelines on AWS and Databricks, architecting storage solutions and optimizing ETL workflows for analytics and reporting.
Build and maintain scalable data pipelines on AWS using PySpark, Glue, Lambda, and Terraform, while automating deployments with CI/CD.
Designs and builds scalable AWS data pipelines using Glue, Redshift, and S3, implementing ETL/ELT workflows and optimizing for performance and reliability.
Design and build scalable cloud data pipelines and lakehouse architectures for a government project, using Python, Spark, Kafka, and AWS services.
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.
Design and build cloud-based data analytics infrastructure using AWS, Databricks, and IDMC, migrating and modernizing healthcare data pipelines and ETL workflows.
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