Charles Siu Email and Phone Number

• Lead the development effort of the auto reconciliation project used by internal finance users to perform reconciliation between numerous banking data sources.• Developed and maintained the validation framework used by internal finance users to perform validation checks on numerous data sources for IFRS 17 reporting.• Developed and maintained various data pipelines to perform data ingestion, transformation and archival in the internal data lake and data warehouse using Amazon Lambda, Amazon Glue and Amazon S3, from data sources such as report data from Oracle GL using ESS jobs.• Applied DevOps best practices to project repositories by using Amazon CloudFormation, Amazon CodePipeline and Amazon CodeBuild.

• Developed and maintained the internal integrated big data development platform, which allows data warehouse engineers to build data pipelines for internal company data aggregation, as well as BI engineers and analysts to make ad-hoc queries and build business reports.• Led the effort of redesigning and developing the scheduling engine, which is used to compute task executions based on time of day and task dependencies, in the integrated big data development platform.• Developed and maintained the internal data platform, which forwards the JSON payload of third-party HTTP requests to internal Kafka clusters for further processing.• Led the effort of localizing various internal data products co-developed by mainland China colleagues and provide support to colleagues based in Hong Kong and various other locations.• Led the cloud migration of the internal integrated big data development platform from AWS to Azure.

• Designed and implemented data parsing and transformation scripts in Python for Apache Airflow workflows, including XML and JSON to CSV conversion scripts, which are used for data ingestion in cloud databases.• Developed and integrated Informatica ETL workflows and mappings for business layers in the cloud data warehouse, which simplify OLAP queries for analytics and optimizations.

• Tackled the problem of classifying a backlog of 100K+ unknown internet domains generated by Valimail Defend.• Developed an end-to-end machine learning pipeline in Python that classifies domains by detecting whether they belong to low-risk categories such as real estate. The Gradient Boosting Machine (GBM) model achieved a 95%+ precision rate with test data when classifying real estate domains using Natural Language Processing (NLP) for web content analysis. Going into production, the pipeline greatly reduced the reliance on manual data labeling.• Designed and implemented RPC APIs using Flask in Dockerized modules in the pipeline.• Built web scrapers using BeautifulSoup to gather multiple external data sources for ML model training.

• Designed and Developed REST APIs with Java in the backend module of the Intelligent Advertisement Management Platform project.• Implemented DevOps such as CI/CD with Jenkins and GitLab CI in the development environment. Improved productivity by eliminating the need for manual image building and deployment.• Integrated service mesh management with Istio on Kubernetes and presented the topic to team members.• Designed Kibana dashboards for metric aggregation and distributed tracing in the development environment.• Maintained workstations and server equipment for software development and client demonstration. Coordinated with the project manager for equipment procurement.

• Administrated and Maintained the website of USF China Business Studies Initiative.• Designed brochures and other printed materials for events organized by CBSI, including 4 issues of KCBSI, the bi-annual news bulletin published by CBSI.• Participated as a student ambassador in numerous events organized by CBSI.

• Performed quality control tests for in-house software applications integrated with Cisco Unified Communications Solutions.• Developed and Presented a demo application integrated with Cisco Jabber Web SDK.