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Salvador Guzmán

@salvadorguzmn

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Data Engineer with 4+ years building reliable multi-cloud data platforms using Python, SQL, dbt, and Airflow.

El Salvador

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What I'm looking for

I’m looking for a team that values reliability, cost, and performance in multi-cloud data platforms—where I can own pipelines, dimensional models, and automated data quality. I also want to apply MCP/LLM automation to warehouse design, lineage, and operations.

I’m a Data Engineer delivering production data platforms across Google Cloud and Azure—building batch and streaming pipelines, dimensional warehouses, and automated data quality at scale. I focus on reliability, cost, and performance in multi-cloud environments.

At Applaudo Studios, I’ve designed and deployed end-to-end data products from 10+ enterprise sources, processing millions of records daily with SQL and Python. I establish data SLAs and operational runbooks, cut warehouse query costs and scan volume by ~40%, and reduce downstream errors by ~70% using schema-drift detection and automated validation.

Currently, I’m building MCP-based AI agents to automate warehouse design, lineage, and operations—while staying grounded in robust governance, testing, and maintainable modern data stack practices.

Experience

Work history, roles, and key accomplishments

Current

Data Engineer

Current

Applaudo Studios

Jan 2023 - Present (3 years 6 months)

Designed and deployed production-grade batch and streaming data pipelines across Google Cloud and Azure, delivering analytics-ready data products from 10+ enterprise sources. Improved reliability and reduced costs by tuning dimensional models, implementing schema-drift detection, and automating data-integrity validation.

Google Cloud Azure Data Pipelines Batch Processing Streaming Pipelines SQL Python Dimensional Models Partitioning Query Optimization Scan Pruning Schema Drift Detection Operational Runbooks Pytest Great Expectations

Data Quality Engineer

Applaudo Studios

Nov 2021 - Dec 2022 (1 year 1 month)

Automated data and API validation pipelines with Python to reduce manual validation effort and improve CI/CD reliability. Defined validation standards using JSON schema contracts and performance thresholds, and performed root-cause analysis to implement preventative measures.

Python Data Validation CI CD Authentication Root Cause Analysis