Quarterspot is in the Lending business and I am in charge of the Data Warehouse strategy. It is a greenfield environment in which I am building from scratch data pipelines to automate both, ingestion and data model creation, for Data Vault 2.0. In addition, we are taking Quarterspot's AI (proprietary credit scoring, probability of default, bank transaction categorization, and more) and wrapping it as a SaaS product. My role in this initiative is to build data pipelines to process bank partner's data, generate curated data sets, and put them through our ML models to finally come out with key insights that partners can use to create revenue streams or improve existing.Main tool kit:Python, Spark, Databricks on Azure, Hadoop on Azure HDInsight, Presto, SQL Server MI, Talend, Java, Powershell, Terraform.

Multi-terabyte enterprise warehouse serving more than 1,000+ Hotels with state of the art reporting and analytics capabilities. My role is to lead a team of a diverse offshore/onshore ETL & BI developers to build and maintain scalable ingesting processes, dashboards and a self service BI platform. In this demanding hospitality industry changes occur every minute and therefore at Starwood I strive to deliver products with strong foundation and easy to adapt.Some technologies/tools include but not limited to:Microstrategy 10.1 / 9.1.4, Tableau 9.2, Oracle 12c/11g: PL/SQL, Java 1.6, Hive 0.13.1 on Amazon EMR, UNIX Shell, Informatica PowerCenter 9.1

-Massaging and creating data layers to support reporting platform using Informatica PowerCenter 8.1.1-Creating dynamic reports for different business units, using Microstrategy 8.1.1

Built a DW sourcing 6 city systems using ETL best practices in Talend, PL/SQL and Oracle DB.

Local Law 34 (No Pay to Play) was enacted to basically regulate campaign contributions from individuals who do business with New York City. This law mandated the creation of a Doing Business Database (DBDB) containing the names of entities, their principal officers, owners and senior managers that conduct business with the City of New York. The project covered a public web site (https://www1.nyc.gov/dbnyc/) that searches the DBDB. The DBDB is an outstanding data warehouse model, populated with efficient ETL processes that extract raw data from several different sources such as legacy systems, text files and MSSQL tables. Once the staging area is loaded, a long batch process is launched which encapsulates very complex business rules dictated by the Campaign Financial Board (CFB). I acted as the principal oracle developer who coded these business rules in the DBDB backend. The resulting system was certified by CFB, the Mayor’s Office and DoITT.

Responsible for administering, designing, building, and implementing technology platforms in order to support executive business decisions. I acted as the Principal Technical Lead for all the “Financial Data Warehousing” efforts within this financial group aka BanReservas.Created data model and data conversion plans.Built ETL scripts.Implemented OLAP cubes.Built application to navigate through OLAP cubes and Reporting.Developed in-house Profitability Client System, Budgeting System and Strategic Planning Tool.Technologies include: Oracle PL/SQL, Unix Scripting, DTS, Discoverer, Microsoft Analysis Services, .Net, Crystal Reports.

I was in charge of the analysis, design and implementation of a Software Solution oriented to Streets & Buildings Construction. The project involved using complex engineering calculations in addition to various modules like budget, finances, inventory, payroll, accounting and payments.