Rodrigo Abdo Email & Phone Number

State Of São Paulo, Brazil

São Paulo, Brazil

Leading the Global Data Platform Engineering team, responsible for improving, maintaining, and deploying new data services within our modern data stack. Our global data platform is built on GCP (BigQuery and Dataform) and predominantly utilizes open-source tools (Airflow, Airbyte, and OpenMetadata) and SAP HANA. We also leverage a robust, scalable data platform running on Kubernetes infrastructure.The team is organized into two verticals: Data Platform and Data Engineering, comprising over 20 members across multiple time zones (LATAM, North America, and Europe). Together, we support the entire data stack and manage data projects globally.

São Paulo, Brazil

Responsible for lead data projects in business areas and special projects.

São Paulo, Brazil

Reporting directly to the CEO, my goal is to be close to the teams and leaders responsible for the business areas to provide the best-in-class data product.The data team was divided into four different verticals: Data Platform Engineering, Analytics (Analytics Engineering + Data Analytics), Data Science, and Data Governance. We implemented the data platform, the data lake, 11 data services, dashboards, KPIs, business rules, and a governance program to increase the data quality and ensure the company’s compliance with LGPD.Working with the business areas, we’ve been improving the data-driven culture in N26 Brazil and the businesses results. They were responsible for every data subject in the area. As a result, we’ve seen the data team working as a strategic pillar for the company, providing solid results and moving the needle.Some Data Products & Business Impact:Marketing - we released many data products that helped to improve the conversion funnel, increasing MAU and avoiding lapsed customers. For example, RFM, FT-MAU Predictor, Pre-Lapsed ML Model, and Customers Segmentation for CRM;Credit - developed the first version of a machine learning credit model that helped to maintain the credit limits using external and internal data;Finance - provided many data models to keep the bank conciliation running smoothly; also, we developed a machine learning model that predicted and optimized the company's cash flow, resulting in finance revenue;Product - once we had all app events, the data team could provide different data analyses to measure the new features or products. For example, we could understand the gaps in the onboarding process and increase the results;Compliance - developed different regulatory reports, avoiding new costs and increasing internal efficiency;AML - different data models (e.g., risk matrix) and data integrations were released with third partners, supporting the AML team in tracking and preventing fraudsters among the customers.

Mexico, Colombia, Peru, Ecuador, Dominican Republic And Europe

I led the data engineering team responsible for the fintech ventures in Brazil (Donus), Middle Americas (SíHay MX, Colombia, Peru, Ecuador, and Dominican Republic), and Europe. In those countries, one of my team's goals was to collect data from several data sources that would be used for the credit models developed by the global data scientist team. The credit model developed by Z-Tech was more accurate and produced better results than the local credit models. We bring different ventures to use our global data platform, Iguazu. All the venture data and machine learning models were in one place. The team was fully connected with the local business intelligence teams, providing different data services for business areas, such as data integrations with 3p, data models, data products, and machine learning models. Finally, I had the opportunity to lead people from different countries like Brazil, Mexico, and India.

São Paulo, Brazil

At the Global Team, Iguazu (Z-Tech's data platform) became global; more Z-Tech ventures were evangelized to use Iguazu. We migrated the entire data platform from AWS to Azure in a few weeks, adding new data services and giving more autonomy to the business users and stakeholders. This reduced costs and increased the business's value. With a new data platform, we provided new data services for other data roles, especially data scientists, who could create their models and deploy them in our infrastructure. We had the opportunity to implement a data governance program to keep Iguazu compliant with LGPD and GDPR policies. Also, I was the Data Engineer responsible for fintech services and initiatives across the LATAM. Donus in Brazil (www.soudonus.com.br), was one of them.

São Paulo, São Paulo, Brazil

As part of the Donus data engineering team, we were responsible for improving the local data platform (running on AWS) and keeping all data services (Apache Airflow, AWS Services, PowerBI) running smoothly. We developed different data orchestrations to collect data from several transactional sources (from the Donus App); those data were cleaned and prepared to be consumed by the internal key users. Also, we were deeply connected to the business areas; we built different data models using their requirements to create great solutions for their areas, resulting in better business decisions.Finally, we also had the task of evangelizing Donus users to use the full potential of the data platform. To give them more autonomy, we provided extensive SQL and Python classes.

São Paulo Area, Brazil

I was responsible for developing and improving the data platform architecture (Klabin data lake). My goal in the data platform was to create the first data orchestrations from the ERP and other legacy systems to feed the data platform. We also brought more internal areas (HR, Finance, Maintenance) to use the data platform, fostering its use and creating more initiatives across the company. One of the user cases was the first data pipeline from the pulp site. We collected data from several machine sensors, cleaned it, and stored it on the data platform for key users to query. In the future, those data sets would be used as part of the maintenance machine learning model to predict when the machine would stop or break.

São Paulo E Região, Brasil

I was responsible for keeping everything running smoothly in the SAP BW Platform, focusing on the Financial (FI), Stock (MM), Human Resources (HR), and Sales (SD) data. Fully close to the business areas, I led projects and enhancements, which included developments in reports, queries, dashboards, data modeling, and data-flows (LSA Architecture), using SAP products (ECC, BW, BO, IP, and ABAP) and CISCO Composite. I also solved tickets opened by the business areas and monitored the BW (data loads) and BO environments. I developed projects in governance like standards and documents for the BI Area and the Housekeeping (ChangeLog and PSA) of the entire BW environment.

São Paulo E Região, Brasil

As a BI Consultant, I was allocated at Grupo CCR (Jundiaí, Sao Paulo) in a data project for the Planning Area (CCR Actua). We collected data from several internal services, developed data models along with internal stakeholders, and provided different reports for internal teams to consume. It was a huge step; we added a terrific value once they were using traditional spreadsheets to track everything they had. We used the best-in-class SAP services, SAP BW on HANA (LSA and LSA++ Architecture), SAP BPC, and Analysis for Office.

São Paulo E Região, Brasil

As a BI Intern, I was able to develop my knowledges in SAP BW on HANA (LSA Architecture and ETL), SAP BPC and SAP BO 4.x. With a coworker, we were responsible for monitoring the SAP BW data loads and the SAP BO environment. Working in BI Projects, I developed: Reports (WebI), Dashboards (Xcelcius), Bex Queries, BW models, BW/BO roles and the BI Governance (documents and standards). I was also able to lead enhancements and small projects like SAP BO Migration (4.0 to 4.1) and the BW Housekeeping (ChageLong and PSA).

São Paulo E Região, Brasil

Responsible for the financial control, bank interface, analysis and control of cash flow, electronic invoicing (NFe), billing documents and payments.

Master Of Business Administration - Mba, Analytics In Big Data

Bachelor’S Degree, Computer Science