Led the cloud architecture design discussions and coordinated with developers to implement essential configurations in the Databricks platform, including external data sources, storage credentials, Unity catalogs, cluster resource allocation, access control lists, and service principal integrations, ensuring seamless workflow for the development team.

Played a crucial role in developing and maintaining big data ingestion pipelines, contributing to data processing and transformation, which facilitated efficient data analytics and reporting.

Acted as a data steward within the organization, bridging the gap between business stakeholders and developers, aligning data strategies with business objectives, and guiding the team toward achieving project goals. Additionally, served as a Code Review Lead and Technical Lead, providing expertise and leadership to the development team, fostering code quality and best practices throughout the project.

Data Architect Manager

Responsible for overseeing and developing solutions of real time data ingestion using kafka in various aws services. 
Responsible to be Subject Matter Expert in AWS tools and services for project guidance on multiple sectors. 
Worked extensively with AWS Services to manage the connection between producers and consumers for manufacturing data and commercial data.
Collaborated in the design and implementation of streaming solutions in the cloud. 
Orchestrated jobs in databricks, and sagetmeker using airflow and mwaa to monitor DAG structure and execution.

Senior Cloud Data Engineer (AWS SME)

Volkswagen de México

Responsible for laying the foundation of a data initiative in Mexico by being the first data professional hired by Volkswagen Mexico, and was responsible for designing, building, and implementing the cloud architecture for our data lakes within AWS.
Lead the development of the cloud data lakes for storage, and the development of advanced dashboards using Quicksight for consumption and analyzation to gain as much value from our data as possible. 
Led and trained a team of data scientists and business intelligence specialists on data literacy and best practices in order to increase awareness of data in the country. 
Worked on multiple international integration projects using the following cloud computing services in AWS, such as Glue, Crawlers, DynamoDB, Redshift, Athena, and Quicksight.
Led the development of multiple lambdas for the ingestion, transformation, and upload of data. Deployed code into production environments using GIT and GITHUB. 
Developed source to target mappings and data profiling documentation on our cloud data warehousing in Redshift.
Ran multiple queries on our data lakes to visualize our data using databricks.

Data Lead

Serempre

Data Engineering Consultant

Anheuser-Busch InBev

Worked as a data engineer responsible for building complex pipelines to manage the migration of large databases. Responsible for working and developing ETL processes to process big batches of data as well as data streaming events. Worked as a google cloud platform admin and developer constantly using and working with their services like Dataflow, Cloud functions, Dataproc, Bigtable, Bigqueryto develop complex ETL processes for data migration purposes and create models of data warehouses structures as well as business rules
Responsible for the streaming migration and integration with check-points of data integrity validation of millions of records into our data warehouse in BigQuery. Responsible for establishing a business rule and a data model to integrate sales, invoice, user/client, and a wide range of other data.
As a data engineer was responsible for developing cloud functions that processed data from multiple SQL, and NoSQL database servers. Was responsible for developing pipelines using Apache Beam, Spark, Java, and Python to read data, apply complex transformations, and write data to multiple outputs for our data analytics department. Responsible for administering the data warehouse and generate reports with complex queries using Microsoft Server Management Studio.

Senior Data Engineer

Texas Advanced Computing Center (TACC)

Competed in the rigorous data science and analytics research for social change program organized by the Texas Advanced Computing Center, and the University of Texas at Austin. During the program I was trained to use High Performance Computing and data science tools to analyze the effect Covid-19 has had on Texas’s economy by collecting, and cleaning data in order to create detailed visualizations using Python 3 and Jupyter Notebooks.
Conducted extensive data cleaning and data manipulation using Python's Numpy, Pandas, and SciPy to organize and clean web data for further analysis and visualization. Used Jupyter Notebooks to structure and model large amounts of raw data.

Data Science Research Program

Alxedo

Worked closely with both the CEO and CTO to develop data transformations and data analysis
using SQL, Python, and GCP for user and consumption data. Was responsible for the
maintenance of data warehouses in Google Cloud Platform and the data
manipulation/integration using BigQuery by writing commands and structuring the data into
the desired structure. Was responsible for building solutions in Amazon Kinesis as well as data
pipelines from our Firestore database into BigQuery, our connector to Data Studio.
Developed machine learning models to visualize risk prevention tactics as well as understand
trends within the data in consumption and usage.
Worked as data science lead and was responsible for leading the development of a dynamic
dashboard for the company. Used Tableau, and Data studio to display important information
about the product consumption, marketing, and profits over time. Developed machine learning
models to predict user consumption using Python libraries such as Numpy, Scikit-Learn, and
tensorflow.

Senior Data Engineer (Cloud)

Passionate big data specialist with vast experience working in international integration projects that impact the world with data.

Lead Data Engineer with vast experience leading data teams working with Cloud Computing services and big data processing technologies.  Experienced in the development and deployment of end-to-end data pipelines in production. 

Automation, DevOps, and Cloud architecture experience.

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