Build and improve databases, acquire data, ETL/ELT, big data pipelines and deploy cloud services on projects.

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

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

Worked on transitioning production ELT to a new architecture using new AWS stacks and Pyspark, 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, also using 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 heath public system, using PowerBI and Jupyter Notebook. Gathered datasets from many types of sources, building pipelines, performing exploratory data analysis.

Acted as a Data Scientist for a platform that that seeks more agile deliveries, reduction of operational costs, and improvement of processes.

Used multiple models such as SARIMAX, Decision Tree, LSTM and GMM, for 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 turn-over, IT capability and legal documents categorization.

Tuned models and integrated them with computational capabilities.

Performed anomaly detection for financial illegal operations like money laundering using IsolationForrest and NetworkX to map the relationship between transactions with Spark and PySpark.

Built a Big Data fast-lane architecture for a client in the Events and Productions sector.

Worked on Data Wrangling, Data Discovery, and combining 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.

Acted as a Big data architect, implementing data analytics, reporting using PowerBI, and also working on Data Warehouse architecture.

Gathered data from SQL and imported it into Azure blob storage, using Azure data factory. Used Hive and Pig for querying and generating data reports to Power BI.

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

Acted as a Data Analyst for the major geolocation company in Brazil.

Worked on a billing automation system, T-SQL tuning, data consistency, new billing rules based on traffic signals, Client Attendance Program, and also performed lectures on T-SQL tunings.

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