Building and improving databases, acquiring data, ETL/ELT, Big Data pipelines, and deploying cloud services on projects.

Administering infrastructure solutions to improve data models, increase data accessibility, and foster data-driven solutions for clients.

Implementing monitoring solutions to ensure data integrity, working closely with engineers, product managers, and other stakeholders.

Transitioned production ELT to a new architecture using new AWS stacks, PySpark, and stream services like Kafka, Polaris, and Kinesis, also working with files versions.

Built data producers using Python and Flask with Kubernetes to connect to data sources and stream data.

Analyzed data in Snowflake for custom reports that are created using DBT views scheduled by Airflow.

Worked on developing an analytics environment with Impala and Hive, and used Spark/Python for Machine Learning.

Supported the architecture of environment in AWS with Elastic, MongoDB, Glue, Kafka, QuickSight, R, Jupyter Notebook, Pretos, Apache Hue.

Delivered insights on the public heath system using Power BI and Jupyter Notebook.

Gathered datasets from many types of sources, built pipelines, and performed exploratory data analysis.

Worked on a platform that seeks more agile deliveries, reduction of operational costs, and improvement of processes.

Used multiple models like SARIMAX, Decision Tree, LSTM, and GMM in the food and restaurant segment.

Analyzed large amounts of information to discover trends and patterns.

Worked on cloud and on-premises in financial fraud, financial default turnover, IT capability, and legal documents categorization.

Tuned models and integrated them with computational capabilities.

Performed anomaly detection for financial illegal operations like money-laundering.

Mapped the relationship between transactions with Spark and PySpark using IsolationForest and NetworkX.

Built a Big Data fast-lane architecture for a client in the events & productions sector.

Worked on data wrangling and data discovery and combined legacy data with new business data.

Used Python and Scala to create Machine Learning algorithms for customer profile consumption, promotion directions, and event consumption in real time.

Implemented data analytics and reporting with Power BI and worked on data warehouse architecture.

Gathered data from SQL and imported it into Azure Blob Storage using Azure Data Factory.

Created a messenger service between MSSQL 2014 on Azure to AWS RDS and MongoDB using Kafka and Broker.

Queried and generated data reports to Power BI using Hive and Pig.

Conducted data analysis and delivered lectures on T-SQL tuning for a major geolocation company in Brazil.

Worked on a billing automation system, T-SQL tuning, data consistency, new billing rules based on traffic signals, and client attendance program.

Handled BI support, ETL with SSIS, and billing team support.