Summary
Overview
Work History
Education
Skills
Timeline
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Eugenio Gastelum

Senior Data Engineer
Metepec

Summary

Passionate data-driven engineer with hands-on experience across the full data stack—including analytics, data engineering, and data science. Skilled at assessing existing technical landscapes and designing migration roadmaps to help organizations achieve their data goals. Committed to fostering a data-driven culture that empowers analytics, BI, and machine learning initiatives to drive impactful product and operational decisions.

In addition to my technical expertise, I bring cross-functional business experience in finance, supply chain, and digital marketing—enabling me to align data strategy with business outcomes.

Overview

8
8
years of professional experience

Work History

Senior Data Engineer

ConsumerTrack
Remote - Mexico
11.2023 - Current
  • Served as Technical Lead on a 14-month initiative to migrate the company’s core web traffic ingestion and BI ETL pipelines—enabling real-time ad performance and profit analytics across 100% of revenue-generating verticals.
  • Led the redesign and live migration of ETLs processing over 8 million web events per hour and powering a petabyte-scale data lake—spanning ingestion to datamart creation—while minimizing service disruption and downtime.
  • Replaced third-party infrastructure with in-house cloud solutions, leveraging dbt, Snowflake, Airflow, Kubernetes (IaC), and GitHub Actions for CI/CD; monitored cost impact of processing over 50 billion rows per day on a petabyte-scale database.
  • Built end-to-end observability and alerting, enabling rapid anomaly detection and resolution—preventing multi-hour blind spots that previously disrupted visibility across all business verticals.
  • Collaborated on a cross-functional team of 20+ data, QA and analytics engineers, aligning on architectural decisions and execution for one of the company’s top strategic goals of 2024: a seamless large-scale migration of the entire data reporting ecosystem

Data and Infrastructure Engineer

Umba
Remote - Mexico City
08.2022 - 06.2024
  • Designed, deployed, and maintained a scalable, cloud-based architecture for ETL systems, supporting company products and powering a centralized data lakehouse—handling both batch and event-driven workloads.
  • Built data pipelines across more than 20 data sources with different formats, and technologies, including CDPs (Segment, Fivetran, Zapier), custom API integrations, real-time streaming via Kafka and Kinesis, dbt models, and Spark jobs—coordinated through Airflow and deployed with Kubernetes and Docker on AWS.
  • Engineered cloud infrastructure using CloudFormation for the data-stack ecosystem, provisioning AWS resources such as EMR, EKS, ECR, RDS, Kinesis, Lambda, Glue, Aurora, and more.
  • Led the migration of on-premise infrastructure from an acquired bank into our AWS environment, enabling seamless integration with existing systems and improving scalability and maintainability.
  • Partnered with Analytics and Data Science teams to translate business needs into ETL pipelines, delivering data marts and ingestion systems tailored to their requirements.

Data Engineer

Umba
Remote-Mexico
09.2021 - 08.2022
  • Implemented and maintained more than 10 ETL pipelines using DBT, python and R for several data sources.
  • Evaluated various tools and technologies that got adopted in the company's data stack, in order to serve analytics and DS teams; like CDP tools, data visualization tools and distributed data systems (spark on databricks)
  • Maintained and scaled the analytics ecosystem for data visualization and exploration of data
  • Collaborated with the platform team to create the data platform ecosystem to allow for CICD, deployments on kubernetes and orchestration of jobs and databases
  • Automated routine accounting, sales and marketing tasks using Python and dbt models
  • Fine-tuned query performance and optimized database structures for faster, more accurate data retrieval and reporting.

Analytics Engineer

Umba
Remote-Mexico
02.2021 - 09.2021
  • Modeled and structured data in the analytics warehouse, as well as data modeling for new feature stores to ensure availability and usability by BI and DS teams.
  • Developed 40+ reports and over 100 visualizations used daily by upper and middle management for operational and strategical decision-making across product design, marketing strategy, and operational issues response.
  • Produced performance metrics and revenue insights for lending products, enabling visibility into loan book health and financial KPIs—using SQL and Python across various data visualization and storage platforms.
  • Investigated operational anomalies by tracing issues across data sources—ranging from application bugs to fraud patterns and payment processor irregularities—to identify root causes and drive resolution.
  • Delivered key data insights for investors during Series A fundraising, supporting a successful $15M capital raise.

Data Scientist

Sintec
Mexico City
05.2019 - 02.2021
  • Use of Databricks on multi-node clusters to create and deliver ML models. Including several terabyte-sized tables and sources. By optimizing Spark execution plan, table storage optimization and spark configurations for memory usage. We helped to produce a production-level ML model for inventory recommendations for 2 of the big four leading food and beverage companies in Mexico
  • Approached the business to understand the data and opportunity to deliver, in order to design and evaluate appropriate ML models for a prescriptive algorithm
  • The models evaluated with real data ranged from basic clustering (K-means, DB scan, hierarchical clustering), dimensionality reduction (PCA), distribution tests and tree-based models (decision trees, random forest and XGboost). The final products involved selecting the most appropriate ones and deliver a stack of these models to produce recommendation on inventory policies and production scheduling

Business Analytics Analyst

Sintec
Mexico City
08.2017 - 05.2019
  • Cleaning and statistical processing of terabytes of data for machine learning pipelines using Azure's virtual Machines. In order to deliver tools for forecasting and supply chain planning for top beverage and retail companies in Mexico
  • Reporting and data exploration to aid business decisions and recommendations of business consulting team

Education

Bachelor of Science - Chemical Engineering

Universidad Iberoamericana
Mexico City
06.2018

Skills

Dbt

SQL

Python

Data Science

Analytics

Kubernetes

Airflow

Data warehouses

Spark & Databricks

Kafka

Flink

Linux management

AWS for data stack

Data system Migrations

Data Quality and Auditing

Timeline

Senior Data Engineer

ConsumerTrack
11.2023 - Current

Data and Infrastructure Engineer

Umba
08.2022 - 06.2024

Data Engineer

Umba
09.2021 - 08.2022

Analytics Engineer

Umba
02.2021 - 09.2021

Data Scientist

Sintec
05.2019 - 02.2021

Business Analytics Analyst

Sintec
08.2017 - 05.2019

Bachelor of Science - Chemical Engineering

Universidad Iberoamericana

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Eugenio GastelumSenior Data Engineer