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Data Engineer | Argentina
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I'm a Data Engineer focused on building scalable, reliable systems that transform raw data into business value. With a foundation in analytics and statistical analysis—and current training in cloud computing—I specialize in the infrastructure that powers modern data platforms.
My work bridges the gap between engineering and strategy: from orchestrating robust ELT pipelines and improving data observability, to developing metrics layers and building tools that enable cross-functional teams to move faster and smarter.
Most recently at Peloton Interactive, I improved the reliability of critical data pipelines by resolving schema mismatches and optimizing changelog processing for application security data. At Pager Health, I built real-time dashboards and automated workflows that empowered clinical and operational teams to act on business-critical insights with confidence.
I'm currently pursuing an M.S. in Computer Science at the Georgia Institute of Technology, deepening my expertise in distributed computing, data architecture, and cloud-native systems. I also hold an M.A. in Applied Economics from the University of Houston, bringing a quantitative lens to every technical problem I tackle.
I thrive in fast-paced, ambiguous environments where technical rigor, cross-functional collaboration, and long-term thinking are essential. Whether optimizing Spark jobs, deploying infrastructure with Terraform, or helping teams interpret key metrics, I bring a pragmatic, systems-minded approach to data engineering.
Outside of work, you’ll find me dancing or contributing to open-source projects — like my custom Python package for probability distributions or my real-time data pipeline demos using Flink and Kafka.