Professional snapshot
Data Engineer · Analytics Engineer · Applied AI
Mexico · Remote / International
Currently
Data Engineer
Vascar Solutions
Experience
Data & Analytics
2023 → Present
Background
Industrial Physics Engineering
Data Science concentration
Worked across
Core
01 / Experience
Where I applied it
Vascar Solutions, Auronix, and Totum Talent — with the work, not only the title.
Jan 2026 — Present
Data Engineer
Data engineering consultancy · staffing, then project-based
Mexico · Remote
I have worked both delivery models at Vascar: first staffing embedded with a client team; then project-based ownership of a GCP / BigQuery platform. Different stacks, different ways of working.
Feb 2025 — Dec 2025
MID Data Analyst, Financial Services
Mexico
Worked at the intersection of analytics, product and financial-services operations, modeling conversational and transactional information for reporting and decisions.
Aug 2023 — Feb 2025
Data Analyst, Outbound
Mexico
Supported outbound systems with reporting, ELT collaboration, and product metrics — messaging, behavioral data, and operational analytics.
Nov 2022 — Aug 2023
Database and Project Intern
HR consultancy
San Pedro Garza García, Nuevo León, Mexico
Supported administrative operations at an HR consultancy: Excel and Google Drive for day-to-day files, plus executive presentations for partners and clients.
Professional domains
Data platforms
Multi-source ingestion · modeling · reliability
Marketing analytics
Paid media APIs · web analytics · CSV / JSON · client reporting
Financial services
Messages · status · transactions · product metrics
Outbound systems
Messaging · behavioral data · operational analytics
Applied AI
LLM applications · decision support · experimental systems
Systems & Patterns
Sources
Pipeline
Consume
Decision
INGEST
Land payloads from sources into the system without deciding meaning yet.
Sources
Pipeline
INGEST
Land payloads from sources into the system without deciding meaning yet.
Consume
Decision
Notes on the craft
Systems > tools
02 / Selected work
What I build
Client names withheld when needed. Architecture patterns and engineering surface — not any company's blueprint.
Professional system
2026
Multi-client analytics platform integrating advertising, web analytics and operational sources into a unified warehouse and reporting layer.
Professional system
2026
Late-arriving identity and transactional facts — messages, status events, and transactions — matched over time and processed incrementally with cost control. Client withheld.
Systems with a public repo or a documented experiment.
Applied AI · data platform
01A conversational collections system paired with a Bronze → Silver → Gold pipeline and a live metrics dashboard.
Scientific ML
02Shrink a theoretical formulation space with physics-informed synthetic data, surrogate models, and experiment prioritization.
03 / About
Why I think this way.
I trained as an Industrial Physics Engineer, with a concentration in Data Science — machine learning, data-science principles, and the math and infrastructure around them. Physics still shapes how I work with data: understand the system, identify its constraints, measure, then decide.
I sit between engineering, analytics, and the business question. Pipelines and models are the medium. The point is a decision someone can defend: who to call, what to recommend, what to stop doing.
I care more about grain, incrementality, and whether a number can be reproduced than about collecting tools. Data engineering is how I practice that now. It does not have to be the whole identity.
Outside data: travel, business, cities, science and the systems behind them.
I also help organize Graffito Fest, a hip-hop and rap festival and freestyle tournament in Monterrey. It started in 2025 with Melissa Corona; we've had Eptos and Bizor.
2018
Physics
Tecnológico de Monterrey · Industrial Physics Engineering · Data Science concentration
2023
Data / analytics
Product, outbound and finance teams
2025
M.Sc. Data Engineering
Universidad Complutense de Madrid · Azure (Storage, Catalog, OpenAI, Databricks)
Now
Data Engineering
Data Engineer as the primary role
Measure before optimizing
05 / Stack
Tools I use
AWS, GCP, and Azure — I've shipped work on each. The inventory is tooling, not a certification wall.
TOOLING
SOURCE
INGEST
TRANSFORM
SERVE
06 / Contact
Open to conversations about Data Engineering, Analytics Engineering, Applied AI, and projects that need that mix. Email is the most reliable path.
carloscorona99@gmail.com→
