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São Paulo
Murillo Alves

Murillo Alves

Data Engineer | SQL, Python, Airflow, Spark | AWS

Tecnologia / Internet

São Paulo, São Paulo

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Sobre Murillo Alves:

Data professional with over 3 years of experience in data structuring and modeling, designing data solutions to enable businesses to work with the most efficient information. Proficient in Python and SQL, having applied these skills in diverse industrial and governmental projects, including land management, environment, logistics, and marketing. International experience and effective collaboration in large teams. 

Here are a few examples of my work: 

• Delivered Santa Cruz de la Sierra Smart City Project, which impacted up to 2 million people. 

• Presented Dam Break Emergency Action Plan Project for Brazilian governmental agencies, that impacted the people of 8 cities. 

I am currently gaining deeper expertise in Relational and NoSQL databases, data pipeline development, data orchestration, and Cloud Computing, using tools such as Postgres, MySQL, Apache Cassandra, Apache Stark, Apache Airflow, and AWS. I aim to use this knowledge to perform problem-solving and meet the best data solutions. 

Additionally, in 2022, I went on a cultural exchange in Europe. During the trip, I interacted with people from different backgrounds, listened to their stories, and gained a better understanding and appreciation of their cultures, broader worldview, and greater self-awareness. 

🤩 I get excited about opportunities where I am able to work with data that will positively impact people’s life. 
 

Experiência

Analytics Engineer at SAI Brasil, a Geotechnology company providing spatial data survey services and related projects, where I:

• Delivered the Santa Cruz de la Sierra Smart City Project, which impacted up to 2 million people. Co-managed and trained a team of 12 new employees for efficient data collection. 

• Ensured access to crucial and consistent information by extracting, loading, and integrating data from various sources into SQL database and EDA processes including cleansing and validation.

• Increased data efficiency and accuracy by 50% by implementing Python scripts to automate error handling and identification across multiple projects.

• Accurately analyzed 50+ data attributes using SQL and ArcGIS (when spatial data), which enabled efficient statistical reporting, data visualization, and KPI monitoring in Power BI.

Educação

Federal University of ViçosaBrazil — Bachelor of Engineering (Introduction to Programming I Monitor)

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