Description

I prefer not to box myself as just a Data Engineer.

I can develop a backend for a data integration project.

I can deploy it and build a CICD pipeline for it.

I can design the data architecture for complex systems and businesses.

I can code and maintain the ETL pipelines that feed it.

And I can do all of that for geospatial data and applications.

I am available for work in either EU or US East timezones.

Languages

Spanish
Native or bilingual
English
Fluent

Workplace preferences

Can work on-site

Madrid (up to 50km)

Xcalibur Smart Mapping
Data Engineer
May 2024 - Today (2 years and 1 month)
• - Leading the development of the data integration module for the XENAI geospatial platform using Airflow and Airbyte.
• - Engineering the geospatial query layer for XENAI by adapting Trino to support high-concurrency spatial analysis on petabyte-scale datasets.
• - Designed and led the development of a Geospatial Lakehouse, architecting pipelines for both vector and raster data using Databricks, Spark, Oracle Cloud.
• - Developed and containerized inference endpoints using Django and Docker, deploying backends to Azure VMs via Nginx and GitHub Actions CI/CD pipelines.
• - Built ML models for automated geophysical data processing and interpretation with PyTorch to significantly reduce manual overhead. Used MLflow for experiment tracking.
• - Optimized field Quality Control (QC) processes by implementing automated workflows with Prefect.
Python CI/CD Management Cloud Platforms and Infrastructure GIS SQL
PwC
Data Consultant
September 2023 - February 2024 (5 months)
• - Built financial data pipelines and yield curve calculators for a banking client (SSIS, Python).
• - Modeling and implementation of the Lakehouse for a sporting client (Azure Data Factory, Databricks, Spark).
• - Modeled Data Mart for a web app (SQL Server ).
• - Development of financial dashboards for banking clients (Dash).
Python Apache Spark Databricks Data visualization Model Training and Evaluation
SAS Institute
Data Intern
September 2022 - January 2023 (4 months)
• - Development of a predictive maintenance model for an industrial ventilator (SAS, SAS Viya).
- Experimented with unsupervised outlier detection models (Python)
Python Model Training and Evaluation Data visualization