维克多·爱德华多·帕托·保利罗，开发商在<s:1>圣保罗州-巴西圣保罗州
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Victor Eduardo Pato Paulillo

Verified Expert  in Engineering

Data Engineering Developer

Location
São Paulo - State of São Paulo, Brazil
Toptal Member Since
March 8, 2021

Victor是一名数据工程师，在金融科技和教育科技市场拥有六年的经验, building data warehouses, data pipelines, modeling, analysis, dashboards, and marketing campaigns. 他是Python和大数据分析方面的专家，在实施和维护CRM平台方面拥有产品负责人的经验.

Data EngineeringSQLData AnalysisData AnalyticsData WarehousingData Warehouse DesignData QualityApache AirflowETLApache HivePandasAgileBusiness Intelligence (BI)HDFSPython

Portfolio

Chegg - Toptal
Redshift, Databricks, SQL, Python, api, Pandas，数据管道，数据建模...
StoneCo
Apache Airflow, Apache Kafka, Hadoop, Apache Hive, ETL, Python...
Banco Original
Apache Airflow, Agile, Google Cloud Platform (GCP)， ETL, Google Pub/Sub...

Experience

SQL - 5 yearsData Engineering - 4 yearsETL - 4 yearsApache Airflow - 4 yearsAmazon Web Services (AWS) - 3 yearsBusiness Intelligence (BI) - 3 yearsGoogle BigQuery - 3 yearsPython - 3 years

Availability

Part-time

Preferred Environment

Apache Airflow, Google Cloud Platform (GCP), SQL, Python, Business Intelligence (BI), ETL, Databricks, Amazon Web Services (AWS), Tableau, Redshift

The most amazing...

...我创建的是一个系统和一个仪表板，它可以自动获得20多种金融产品的营销活动的转化率.

Work Experience

Data Engineer

2021 - PRESENT
Chegg - Toptal
  • 通过分析30个现有报告和120个表，对客户端的数据仓库中的数据进行分析和建模.
  • 在Databricks上创建Python作业，从供应商的API获取数据，并通过数据质量和过程控制将其加载到Redshift表中.
  • Built, modeled, 并在Databricks上维护数据管道，将数据加载到Redshift和Tableau Server. 创建了一个包含20个表的数据集市结构，支持50多个Tableau报表.
  • 开发了一个数据质量框架，在客户端的数据管道和一个Tableau报告之后运行，以显示和警告数据的任何问题.
  • 通过构建营销表的数据管道，将Looker上10个表的数据结构迁移到Tableau Server.
Technologies: Redshift, Databricks, SQL, Python, api, Pandas，数据管道，数据建模, Data Warehousing, Data Marts, Tableau, Dashboards, Amazon Web Services (AWS)

Data Engineer

2021 - 2021
StoneCo
  • Created batch and streaming data pipelines for business teams.
  • Loaded data from external data providers on the Data Lake.
  • Created a data quality system for data processing jobs.
Technologies: Apache Airflow, Apache Kafka, Hadoop, Apache Hive, ETL, Python, Amazon S3 (AWS S3), Redshift, SQL, ELT, Data Quality, Data Processing, Jupyter Notebook, Pandas, NumPy, Data Engineering, Data Modeling, Data Architecture, Data Warehouse Design, Data Warehousing, Financial Data, Data Pipelines, Data Marts, Banking & Finance, Amazon Web Services (AWS), Amazon Athena, Data, ETL Development, Data Science, Docker Compose, Docker

Data Engineer

2019 - 2021
Banco Original
  • 使用Google Cloud Storage将10个本地ETL进程迁移到Google Cloud Platform, Cloud Functions, Google Pub/Sub, and Google BigQuery.
  • 利用Hive和Power BI为20多个金融产品和每月约100个活动开发系统. 这就自动得到了营销活动的转化率, specifically email, push, and ads,.
  • 创建了一个与BigQuery数据集成的API，使用谷歌云平台工具:BigQuery在Facebook营销API和谷歌广告上发布, Cloud Function, and Pub/Sub.
  • 作为产品负责人和开发人员，创建数据管道和数据建模，以支持新收购的营销平台, Oracle Responsys, and adapt it to the company.
  • 与产品经理合作，获取有关事务数据库的正确信息，并将其开发为数据仓库的ETL.
Technologies: Apache Airflow, Agile, Google Cloud Platform (GCP)， ETL, Google Pub/Sub, Google Cloud Functions, Google BigQuery, Facebook Marketing API, Google Ads API, ELT, Data Warehouse Design, Data Warehousing, Data Lakes, Financial Products, Financial Data, Product Owner, Oracle Responsys, Jupyter Notebook, Cloud Computing, Google Cloud Composer, Data Pipelines, Apache Hive, HDFS, Hadoop, Zeppelin, Python, SQL, Pandas, NumPy, Data Quality, Data Processing, PyCharm, Functional Programming, Data Engineering, Data Modeling, Data Architecture, Apache Spark, Google Cloud Storage, Data Marts, Banking & Finance, Data, ETL Development, Data Science

Business Intelligence Analyst Jr

2017 - 2019
Banco Original
  • 支持HDFS上数据湖环境的开发和结构.
  • 在位于数据湖(HDFS)的数据源上开发了15个ETL进程. Delivered them on Hive for analytics purposes to business users.
  • 与市场经理合作，通过深入分析客户行为，制定数据驱动的销售策略.
  • 开发供销售和产品团队使用的产品性能仪表板.
  • 根据产品分析规则，为营销活动旅程创建了超过20个客户受众.
  • 通过对JSON文件的分析改进了客户服务聊天机器人的性能.
  • 与业务和产品团队合作，传播分析最佳实践, improve their query performances, and get the correct rules to achieve their analysis goals.
Technologies: HDFS, Hadoop, Zeppelin, Apache Hive, ETL, Chatbots, Data Analytics, Business Intelligence (BI), ELT, Financial Data Analytics, Financial Data, Financial Products, Marketing Automation, Jupyter Notebook, Microsoft Power BI, Marketing Campaign Design, Data Auditing, Sales Strategy, Data Lakes, Data Warehouse Design, SQL, Python, Data Quality, Data Processing, Data Engineering, Data Modeling, Data Warehousing, Data Marts, Banking & Finance, Data, ETL Development, Data Science

Business Intelligence Intern

2016 - 2017
Banco Original
  • 创建报告来分析客户的可租性和获取情况.
  • 与产品经理一起审核分析数据库上的十种金融产品，并将其与事务系统进行比较.
  • 使用SAS Guide软件，使用SQL和SAS开发了大约20个特别查询.
  • Created around 25 top campaigns through several fonts of data (e.g., customers that delay the credit card bill).
  • 开发了10个金融产品数据库的数据字典.
  • Supporting the survey and control of informational data gaps.
  • Strong knowledge of flux, rules, and specifications of bank products, like credit cards, loans, 透支来审计基地，创建活动和报告.
Technologies: SQL, SAS Enterprise Guide, Dashboards, Excel 365, Marketing Automation, Financial Products, Data Analytics, Business Intelligence (BI), Financial Data, Financial Data Analytics, Banking & Finance, Data

A Post on BigQuery Data on Facebook Marketing API

http://victor-paulillo.medium.com/post-bigquery-data-on-facebook-marketing-api-276516566bbe
This project connects BigQuery with Facebook Marketing API.

本文展示了该项目的简化版本，并提供了如何在Facebook Ads上发布数据，这些数据可用于为广告定位建立受众，或设置为离线转换.

Upon completing the project, 它可以深入研究客户分析和机器学习模型，以提高广告效果和涉及Facebook广告的新营销策略.

离线转换使Facebook机器学习能够更好地了解您公司的最佳客户, 尤其是当你的产品和服务不是在网上分发的时候.

巴西政府公司注册开放数据集的数据管道

一个数据管道，以加载开放的数据集在云SQL Postgres数据库, 维护一个后端微服务，并通过agenda网站和移动应用程序成为美国云SQL Postgresle.
I was the only developer to build this process, 这是从用Docker在VM上组装气流环境开始的, downloading, 以及对谷歌云存储上巴西政府公司注册的开放数据集的分析, the transformation of the dataset into a table using BigQuery, data quality validations, and loading the final table into Postgres table with Cloud SQL.
所有这些步骤都是在每周安排的气流DAG上创建的.

Languages

SQL, Python

Other

Data Engineering, Google BigQuery, Google Data Studio, Data Analysis, Google Pub/Sub, Google Cloud Functions, Dashboards, Marketing Automation, Financial Products, Data Analytics, ELT, Data Warehousing, Agile Sprints, Financial Data, Financial Data Analytics, Marketing Campaign Design, Data Auditing, Data Quality, Data Warehouse Design, Data, ETL Development, Statistics, Economics, Engineering, APIs, Excel 365, Chatbots, Cloud Computing, Sales Strategy, Product Owner, Data Marts, Data Processing, Data Modeling, Data Architecture

Libraries/APIs

Pandas, Google Ads API, Facebook Marketing API, TensorFlow, NumPy

Tools

Apache Airflow, Microsoft Power BI, BigQuery, PyCharm, SAS Enterprise Guide, Google Cloud Composer, Amazon Athena, Tableau, Docker Compose

Paradigms

敏捷，商业智能，ETL，管理，函数式编程，数据科学

Platforms

Jupyter Notebook, Google Cloud Platform (GCP), Oracle Responsys, Amazon Web Services (AWS), Databricks, Zeppelin, Apache Kafka, Docker

Storage

Apache Hive, HDFS, Data Lakes, Redshift, Google Cloud Storage, Data Pipelines, Amazon S3 (AWS S3), PostgreSQL, Google Cloud SQL

Industry Expertise

Banking & Finance

Frameworks

Hadoop, Apache Spark

2014 - 2019

Bachelor’s Degree in Production Engineering

Federal Institute of São Paulo (IFSP-SPO) - São Paulo, Brazil

OCTOBER 2020 - PRESENT

Modernizing Data Lakes and Data Warehouses with GCP

Coursera

SEPTEMBER 2020 - PRESENT

Google Cloud Platform Big Data and Machine Learning Fundamentals

Coursera

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