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engraulleite/README.md

Welcome to my GitHub profile. ilustração de um computador

About:

Data Engineer with solid experience in designing, building, and optimizing scalable batch and streaming data pipelines, supporting Business Intelligence, Analytics, Machine Learning, and Artificial Intelligence initiatives. Proven track record working in Big Data and cloud environments (AWS, Azure, and GCP), with strong expertise in modern tools such as Apache Spark, Kafka, Databricks, Snowflake, MongoDB, PostgreSQL, and Elasticsearch.

With experience collaborating in agile, cross-functional teams, and holding a background in Engineering along with an MBA in Project Management and BIM, I combine strong technical expertise with a strategic mindset, delivering data solutions that drive efficiency, innovation, and business value.

Summarily, my curiosity extends to the domains of Machine Learning, Artificial Intelligence, Data Engineering, and new technologies. I am always enthusiastic to embrace innovations.

Tech Skills:

-Cloud Computing (AWS, Azure, GCP) - Big Data - Data Warehouse - Data Lake - Data Lakehouse - IaC (Terraform) - Docker, Kubernetes - PostgreSQL - pgAdmin - ETL x ELT pipeline - Python -PySpark - SQL - Google BigQuery - Amazon Redshift - AWS Lake Formation - AWS Cloud Formation - Amazon S3 - Amazon EMR - Amazon Athena - AWS Glue - Data Modeling - Data Quality - Data Lineage - Apache Hadoop HDFS - Apache Hadoop YARN - Apache Spark - Apache NiFi - Apache Kafka - Apache Airflow - Apache Zookeeper - Airbyte - Batch and streaming data acquisition - Data Lake On-premises - Data Lake AWS - Databricks - Snowflake - Dremio - Metabase - Looker Studio - Kerberos Security Protocol - PENTEST - Kali Linux - Linux

How to reach me:

Linkedin

Popular repositories Loading

  1. engraulleite engraulleite Public

    My personal repository.

  2. Local-Data-Warehousing-with-Docker Local-Data-Warehousing-with-Docker Public

    Creating a DW from 0 to hero. Starting with logical and physical modeling to valuable reports.

  3. AWS-Cloud-Data-Warehouse-with-IaC AWS-Cloud-Data-Warehouse-with-IaC Public

    Creating a Data Warehouse in AWS Cloud with all infrastructure created by code (IaC) through Terraform

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    In this project we build a Data Lake On-Premises using containers Docker and batch data ingestion using Apache Nifi. After the data ingestion, we did the ETL process to load in an Data Warehouse

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  5. Cloud-Data-Lake-with-AWS-Lake-Formation-and-Analysis-via-SQL Cloud-Data-Lake-with-AWS-Lake-Formation-and-Analysis-via-SQL Public

    Using raw data in Parquet format, the Data Lake is built and configured, creating the data catalog,extracting the schema with metadata and analyzing with SQL Language

  6. -AWS-Lake-Formation-with-CloudFormation -AWS-Lake-Formation-with-CloudFormation Public

    AWS CloudFormation stack with IaC. All the resources configured by script YAML. I created a filter for each Data Analyst just visualize the data from your country. The dataset is about Amazon costu…