Rodrigo Sampaio de Sá
Verified Expert in Engineering
Data Engineer & Analytics Developer
São Paulo - State of São Paulo, Brazil
Toptal member since November 25, 2021
Rodrigo is an experienced BI and data consultant as well as a data architect with over 11 years of experience. He has excellent problem-solving skills and the ability to work in a multicultural and agile environment with short deadlines. Rodrigo specializes in business intelligence, data warehouse, data science, analytics, and data visualization. An experienced team leader and project manager, he once efficiently oversaw projects for 10 different clients from multiple sectors.
Portfolio
Experience
- Data Warehouse Design - 11 years
- SQL - 11 years
- ETL - 11 years
- Data Engineering - 11 years
- Data Modeling - 11 years
- Data Analytics - 11 years
- Python - 5 years
- Machine Learning - 4 years
Availability
Preferred Environment
SQL, Python, Data Modeling, Data Warehousing, Data Engineering, Data Analytics, Machine Learning
The most amazing...
...idea I've implemented was an evaluation and optimization model for the company's marketing programs.
Work Experience
Staff Data Science Tech Lead/Engineer
NextRoll
- Expanded the contextual targeting product taxonomy and improved the natural language processing (NLP) model.
- Improved NLP models by fine-tuning neural network parameters and layers.
- Enhanced the contextual targeting product by structuring and refactoring it so that including, excluding, or expanding taxonomy is easier.
- Defined a new way to gather data for NLP projects using zero-shot models.
- Developed APIs to make NLP model predictions available to the whole company.
Senior Data Engineer
Unstoppable Domains
- Developed the ELT process on DBT to model the dimensional model for the data warehouse (BigQuery).
- Developed ingestion pipelines on Airflow and Python to load data from APIs into BigQuery, to later be used as sources on the DBT data warehouse model.
- Created Python scripts to transform data and automate manual processes.
- Created reports on Mode for the financial area and user tracking.
Senior Data Analytics Consultant | Architect
Nordica
- Led and architected the data warehouse of three big pharmaceutical companies. Oversaw the whole process, including gathering requirements, data modeling, ETL processes, dashboard development, and architecture.
- Applied machine learning to predict a company's sales, replacing their current estimates with a considerably better accuracy model.
- Administered optimization techniques to solve the quota distribution problems of a customer.
- Created an evaluation and optimization model for a pharmaceutical company's direct marketing programs.
- Made the creation and maintenance of the dashboard straightforward by creating an architecture that relies on code reusability.
Business Intelligence Consultant
Talent Group
- Architected and developed business intelligence (BI) solutions for seven companies from different segments. Oversaw gathering requirements, KPI definition, data modeling, ETL process, and dashboard development.
- Led the BI area creation of a prominent Brazilian bank's accounting area, overseeing the information that 100 users consumed.
- Created a new architecture to optimize ETL processing and dashboard building with reusable code.
- Got recognized by customers as the go-to problem solver.
Experience
Direct Marketing Evaluation
The first approach I tried to conduct research was creating a dashboard with charts to help them answer questions. That did not work correctly since a doctor could be included and excluded from different programs at different times, making it impossible to have a significant enough sample to analyze. Also, the number of combinations was just too high.
To deal with this problem, I used machine learning to predict the doctors' prescriptions based on whether and how long they participated in the marketing programs. I built this model using XGBoost, so it was somewhat of a black box. To extract the insights from it, I used some machine learning explainability techniques, such as partial plots and SHAP values.
Data Warehouse Architecture
Education
Bachelor's Degree in Computer Science
The University of São Paulo - Sao Paulo, Brazil
Certifications
MCTS SQL Server 2008 – Database Development
Microsoft
Skills
Libraries/APIs
Pandas, XGBoost, PySpark, Spark ML, TensorFlow, PyTorch
Tools
Qlik Sense, Microsoft Access, Apache Airflow, Amazon Elastic Container Registry (ECR), Amazon Elastic Container Service (ECS), Spark SQL, Terraform
Languages
SQL, Python, Python 3
Paradigms
Agile Project Management, Scrum, Kanban, Dimensional Modeling, Business Intelligence (BI), ETL, ETL Implementation & Design
Platforms
QlikView, Alteryx, Amazon Web Services (AWS), Amazon EC2, Docker, Google Cloud Platform (GCP)
Storage
Databases, PL/SQL, Microsoft SQL Server, Relational Databases, Data Pipelines, SQL Stored Procedures, SQL Server Integration Services (SSIS), Amazon S3 (AWS S3)
Frameworks
Spark, Presto
Other
Software Engineering, Programming, IT Project Management, Data Warehousing, Data Warehouse Design, Data Engineering, SQL Server 2015, Data Modeling, Data Analytics, Analytics, Complex Problem Solving, Consulting, Data Science, Architecture, Team Leadership, Data Analysis, Excel 365, Data Architecture, Data Visualization, Dashboard Development, Data Build Tool (dbt), ETL Tools, Data Migration, Technical Architecture, Technical Leadership, Machine Learning, Natural Language Processing (NLP), Google BigQuery, APIs, Generative Pre-trained Transformers (GPT)
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