David Regalado

Hi there!

Thank you for visiting my profile. I am passionate about data & AI. Throughout my 17 years of professional experience I have seen projects of various types, sizes and industries. 

Summary

In my country, I've worked in the biggest companies like:

- Financial Services: Scotiabank, Interbank
- Telecommunications: Telefónica del Perú, Claro
- Consulting: Teradata Perú, Indra, Encora
- Consumer Credit Reporting Agencies: Equifax
- Ad-Tech: Manya.pe

In those companies, I did the whole data lifecycle: data extraction, ingestion, data manipulation, data modeling (normalization, denormalization, etc), data analysis, data quality assessments. In short, the ETL part (data pipelines) + data analysis. 

Achievements: The Data Warehouses/Lakes and dashboards were delivered to my clients, so they could start making data-driven decisions.

These recent years I've been working for U.S. clients as a contractor. Specifically:

- Academics: University of Chicago
- Healthcare: Amplifon
- Cyber Security: Anomali
- Ad-Tech: Clevertech
- Startup: Nebula.io

Achievements: Data pipelines delivered and students gratuated from the University program.

Highlight

- Founder at Data Engineering Latam, the largest, fastest-growing data community in Latin America: https://www.linkedin.com/company/data-engineering-latam
- I taught Python for Data Science in the University of Chicago.
- Recognized as Champion Innovator by Google
- I led teams of 20 people in 3 different occasions.
- Recurrent speaker and jury in events related to data & AI.

Studies

- Systems Engineer from the Technological University of Peru (UTP), tenth superior.
- With a specialization in Data Science from Johns Hopkins University.
- With a specialization in Data Warehousing for Business Intelligence from Colorado University.
- With a specialization in Data Science and Big Data Analytics from MIT.
- With 4 certifications, 15 specializations and 67 Google Cloud Platform digital badges.
- With studies in Artificial Intelligence at UBA-IALAB

Tech stack

Cloud Computing: Google Cloud (GCP), AWS, Azure
Data Engineering: Apache Beam, Airflow, Spark, Databricks, Snowflake, dbt, Hadoop, Hive, Luigi
Databases: BigQuery, Teradata, MongoDB, Elasticsearch, Oracle, SQL Server, PostgreSQL, Mysql
Data Visualization: Power BI, Tableau, Looker, Data Studio
Programming languages: Python, Scala, R
DevOps & CI/CD: Terraform, Docker, Kubernetes, Git, GitHub

Roles 

CTO, CDO, CDAO, Data Science Manager, Data Engineering Manager, Head of Data, Tech Leader, Data Architect, Data Engineer, Data Scientist, BI Consultant.

Ambassador at AI Time Journal

AI Time Journal is a publishing platform that strives to aware users of and around the world of Artificial Intelligence, growing technology trends, and other industry news. Its final aim is to contribute to steering the development of AI for the benefit of humanity.

PepsiCo

Sr Data Engineer

C6 Bank

Responsible for managing the Data Platform Tools.
Management of the existing and evolution of the Data Lake infrastructure and data pipelines.

- Google Cloud Platform (GCP) based data infrastructure responsible for developing and managing the following services:

Google Cloud Storage;
Big Query;
Pub/Sub;
Cloud Functions;
Dataflow;
Google Kubernetes Engine;
Cloud Composer;
Streamsets.

Performing SRE tasks with Git, BitBucket, Ansible, Terraform, Shell, Rundeck and Python.

SRE Data & Analytics

Luxoft

Account:
* Major US FMCG company
Projects:
* Implementing CI/CD and fostering DevOps by using Github, Azure Boards and Azure Pipelines.
* Data integration between a new SaaS platform and the internal data mart using Azure Data Factory
* Handling business logic with Azure logic apps workflows.
* Loading, transforming and presenting vendor data with data factory, SQL databases and Power BI.

Senior Software Developer | Data Engineer

QDOIS - Data Intelligence

Responsible for coordinating the activities of the data engineering team.

Main activities:

* Delivering robust and reliable data pipelines using the Azure Data Platform
* Analysis of requirements with stakeholders
* Designing and architecting the data landscape
* Implementing data governance and data quality metrics
* Ensuring that agile is being practiced by the team members

The main tools used for developing the data products are:

      - Databricks
      - Azure Data Factory
      - Azure Data Lake Storage
      - Azure Logic Apps
      - Synapse Analytics
      - Azure SQL Database
      - Power BI
      - Azure DevOps for CI/CD and project management (Pipelines, Boards, Repos)

Tech Lead Data Engineer

Banco PAN

Data Specialist

Via Varejo SA

- Data ingestion in the Raw and Context layers of the Data Lake (On-premises and Cloud) using technologies such as Apache Kafka, NiFi, Spark, Azure Data Factory and Databricks.

- Maintenance of the Data Lake environment both on-premises (Hadoop) and cloud-based (Azure Data Lake Storage v2)

- ETL and data preparation in databricks using pyspark and SQL API

- Design and architeture of data solutions in Azure Plataform

- Development of specialized views using Azure Synapse Analytics and Power BI

- Data manipulation in MongoDB, Redis, Hive, HBase, SQL Server and DB2.

Data Engineer

Itaú Unibanco

Responsible for the administration of the following tools:

Data integration/ETL/ELT:

- IBM Infosphere DataStage
- Microsoft SQL Server Integration Services
- Alteryx Server
- Oracle Data Integrator
- Informatica (PowerCenter/BDM/BDQ/EDC)

Databases:

- Teradata
- IBM DB2
- MariaDB
- MongoDB
- Sybase IQ
- SAP Hana
-Neo4J

Big Data DBA and Data Integration Analyst

Responsible for leading a Data Science & Engineering squad to meet our business goals. 

Our main objective is to improve the Service Desk Operations and User Experience through the use of high quality data and advanced analytics.

Our activites comprised of:
- Defining the Data Architecture
- Creating the appropriate Data Governance Definitions with Data Catalogs, Documentation, Data Stewardship and Data Quality.
- Ingesting data from different transactional sources (Oracle, SQL Server, MariaDB, Splunk) to the Data Lake (Cloudera Hadoop) using Sqoop, Alteryx and SQL Server Integration Services as data integration tools
- Preparing the data using Alteryx and SSIS
- Exploratory Data Analysis using python, jupyter and libraries such as pandas, bokeh, numpy, matplotlib and seaborn
- Creating dashboard and visualizations to stakeholders and decision making executives in PowerBI and Tableau.

One of our main products is a recommendation system for end users using machine learning and AI.

Data Science Team Lead

Data Governance area with the main responsabilities of

- Provide data solutions to business needs
- Create and manage policies to govern the informational environment
- Protect the information in the Data Lake by monitoring access and usage of data

Data Governance Analyst

Responsible for the automation of operational processes using powershell, SCCM, System Center Orchestrator and Control-M.

SQL Server mission critical administration:

- Performance Troubleshooting and Tuning
- Incident response
- Disaster Recovery strategies
- Administering maintenance jobs
- Environment continuous improvement

DBA  Pl.

SQL Server administration with the main responsabilities of:

     - Performance troubleshooting
     - Maintaining administrative jobs
     - KPIs for database administration
     - Proactive monitoring
     - Disaster recovery strategies

DBA  Jr.

Caterpillar Inc.

Auxílio visual para produção, job rotation, CPS, six sigma fazem parte do projeto de estágio.

Engineering Intern

Saint-Gobain

Desenvolvimento, análise estratégica baseada no método SWOT e caracterização de concretos refratários com foco na diversificação e abertura do mercado.

Intern

I am a Data Engineer who loves the challenges of both the Operational and Analytical areas. Previously, I worked as a Data Science Analyst, focused on the Data Governance Journey in the biggest bank of Latin America. Furthermore, I am also a passionate DBA and SRE enthusiast.

I graduated in Materials Engineering at the Federal University of São Carlos (UFSCar) and I have a MBA degree in Data Engineering at FIAP.



Engenheiro de Dados compromissado em promover a cultura Data Driven na empresa. Anteriormente, atuei como analista de ciência de dados, promovendo a jornada de Governança de dados no maior banco da América Latina. Sou também um apaixonado Administrador de Banco de Dados (DBA) e grande entusiasta de práticas DevOps e SRE.

Formado engenheiro de materiais pela Universidade Federal de São Carlos (UFSCar) e MBA em Engenharia de Dados na FIAP.

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David Regalado

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