Daniel Belchior
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Daniel

Sao Paulo, Brazil id="timeZone">--:--:--

A senior engineer with 15 years of experience providing business intelligence and data science solutions for medium to enterprise clients. Daniel’s an expert building complex ETL processes to consolidate data from multiple sources and leveraging data visualization tools like Tableau and Power BI to build advanced reports, dashboards, and analytical tools.

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Skills
Years
1
2
3
4
5
6
7
8
9
10+
Oracle Spatial
PowerBI
HBase
Tableau
SQL Server
ArcGIS
PostgreSQL
Oracle
NiFi
Hive
Python
Hadoop
HBase
Hadoop
HBase
Developer Personality

Independent

Collabrativer

Trailblazer

Conservative

Generalist

Specialist

Planner

Doer

Idealist

Pragmatist

Abstraction

Control

100
50
0
50
100
Feature Experience

Data Modeling

ETL Systems

Business Intelligence

Data Visualization

Big Data

MODERATE
EXTENSIVE
EXPERT
Cultural Experience

TEAM LEAD

Architect

Consultant

Enterprise

Spatial Data

MODERATE
EXTENSIVE
EXPERT
Portifolio

Itility

Data Engineer

Work Experience : 2015-2020

Acting as a data consultant building data pipelines and ETL processes to extract data from customers devices/machines and integrate it into a common environment. Then transformed and enhanced data for PowerBI. Created advanced reports and dashboards with PowerBI.

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Public Prosecutors Office

Big Data Lead

Work Experience : 2015-2020

Lead for Big Data team focused on data ingestion and analytics, using Oracle Big Data Appliance with Cloudera suite. Developed in Python and provided technical expertise around technologies adopted by team. Owned data pipeline platform development and maintenance, data ingestion, data quality standards, and design patterns.

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Public Prosecutors Office

BI Architect

Work Experience : 2015-2020

Lead for Big Data team focused on data ingestion and analytics, using Oracle Big Data Appliance with Cloudera suite. Developed in Python and provided technical expertise around technologies adopted by team. Owned data pipeline platform development and maintenance, data ingestion, data quality standards, and design patterns.

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