Luciano Pacione Alvez

Data Platform Engineer

Spot2.mx

Dec 2025 - Current (9 months)

Designing and implementing a standardized Bronze/Silver/Gold data framework, building Gold tables that establish a reliable foundation for analytics and future Al agent consumption across Product, Marketing, and Finance teams. Structuring and modeling data into a governed, consistent layer that enables scalable data usage and cross-team insights throughout the organization. Developing and modifying Django-based endpoints used by the company's web platform, providing faster and clearer data insights to end users at key interaction points.

Data Platform Engineer

Ualá

Mar 2025 - Nov 2025 (9 months)

Designed and managed production-grade cloud data infrastructure on GCP (BigQuery, GKE, Cloud Run) using Terraform and Terragrunt, ensuring scalability, reliability, and cost control across data and application services. Developed and maintained Python-based services and data integrations to enable consistent, reliable data flow between upstream systems and core databases within the platform. Led Al/ML platform initiatives with Vertex Al, defining observability and governance standards for data and Al workflows in production environments.

Data Engineer

Datalytics

Jul 2024 - Feb 2025 (8 months)

Designed and implemented a Star Schema data model in Azure Databricks using SQL and PySpark to support business metrics, analytics, and Bl dashboards for a global client. Built and maintained scalable Bronze/Silver/Gold data pipelines, ensuring data quality, lineage, and governance across multiple data sources. Automated ETL/ELT processes for both historical and incremental data ingestion, providing structured and reliable datasets for analytics teams.

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Site Reliability Engineer

ZYZYGY INC

Mar 2022 - Jun 2024 (2 years 4 months)

Managed and optimized large-scale logging and metrics infrastructure (ELK Stack on GCP), centralizing operational data across global environments. Automated infrastructure provisioning and configuration using Terraform, Docker, and Python, improving consistency and deployment speed. Enhanced observability, performance, and reliability of operational platforms by tuning clusters and implementing monitoring best practices.

Luciano Pacione Alvez

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