Adriano Cardoso

Defined big data architecture for the innovation branch of a Brazilian bank, using Azure, Databricks, Python and Spark Streaming to handle near real-time data processing for retail credit risk analysis. Initially, aiming to create the data environment and plan how to migrate the bank’s pipelines.

- Designed a data warehouse solution using AWS services and Terraform to enable faster data processing and cost optimization for the Bank’s Anti Money Laundering (AML) team. - Managed data lake using SQL, Hadoop, and Spark to store, process and create models for AML scoring and analysis. - Developed and supported multiple dashboards using Kibana, Elasticsearch, and Javascript to enhance decision-making capabilities by presenting complex aggregated data.

- Built and managed several data pipelines using Alteryx, Python, Java, and SQL, leveraging on Pandas, Scikit-learn and MLFlow to handle large volumes of data for AML analysis to prevent further illegal use and tarnishing the institution’s image. - Supported infrastructure of data business applications using Linux and Bash to ensure the smooth and efficient operation of the bank’s business processes. - Provided technical and architectural guidance to web applications using Angular, Cassandra and Kafka

- Developed a data extraction/processing pipeline using SQL, Python, and Javascript to measure software development practices for performance evaluation metrics of more than 900 bank employees. - Created a managerial dashboard using SQL and Tableau to measure software development practices considering unit testing, code review, code quality (COBOL and DB2), Source Control Management (SCM), budgeting and planning of internal and external hours.