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Designs and builds scalable AWS data pipelines, data lakes on S3 with Apache Iceberg, and Airflow workflows for CDC and batch ingestion from DynamoDB, Aurora PostgreSQL, and Neptune.
Build and own Duetto’s Python/PySpark data lakehouse that powers real-time hotel pricing decisions, migrating from batch to streaming pipelines on AWS while driving data quality and AI-assisted tooling.
Build and maintain scalable data pipelines and cloud infrastructure on AWS to support real-time and batch processing for a sports-betting business.
Builds and maintains ETL/ELT pipelines and graph databases for telecom and financial clients, using Python, SQL, and cloud tools like BigQuery or Azure Synapse.
Designs and builds data pipelines, warehouses, and analytics systems using Python, Spark, and cloud platforms like Databricks or Snowflake.
Designs and maintains data pipelines, warehouses, and analytics infrastructure using SQL, Python, and AWS services to support reporting and modeling for clients.
Build and optimize AWS-based data pipelines and ML workflows using SageMaker, Kinesis, Glue, and Redshift, ensuring low-latency real-time and batch processing with Python and AWS services.
Builds and maintains scalable AWS data pipelines with Python, PySpark, Glue, and Airflow for a major bank in Sydney.
Lead the design and modernization of a cloud-native data platform for Product Control, migrating legacy SQL Server systems to AWS-native services like Aurora PostgreSQL and Redshift while driving automation and AI-enabled engineering practices.
Build and maintain scalable data pipelines and cloud-based platforms using AWS, Python, Spark, and Databricks to power Sportsbet’s analytics and AI-driven products.
Build and maintain scalable data pipelines and cloud-based data platforms using AWS, Python, Spark, and Databricks to power Sportsbet’s analytics and AI-driven products.
Build and maintain scalable data pipelines and ML models to power Kogan.com’s eCommerce operations, enabling data-driven decisions across marketing, logistics, and finance.
Build and maintain data platforms, pipelines, and ML infrastructure for an asset-management firm, using cloud tools like GCP/AWS and BI platforms such as Power BI or Tableau.
Build and maintain scalable data pipelines, ETL/ELT workflows, and cloud-based data warehouses using SQL, Python, and AWS/GCP tools to support analytics and backend services.
Designs and builds scalable AWS data pipelines and ETL workflows using PySpark, AWS Glue, and serverless components to power analytics and BI.
Build and maintain scalable data pipelines using PySpark on AWS, including ETL/ELT workflows with Glue and Step Functions, serverless automation with Lambda, and IaC with Terraform.
Build and maintain AWS-based data pipelines and warehouses using Glue, Redshift, and S3, with CI/CD and IaC for scalable ETL/ELT workflows.
Build and maintain data pipelines and infrastructure for AI models that optimize Singapore’s transport network, using Python, SQL, Spark, Kafka, and cloud platforms.
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.
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