Felipe Bormann is a Senior Data Engineer with 11 years of experience designing and operating data warehouses, streaming pipelines, and cloud-native analytics platforms across GCP and AWS. He specializes in building reliable, observable pipelines and semantic data layers—using tools like BigQuery, Dataform, Airflow, and Terraform—to balance throughput, cost, and data quality for both batch and real-time workloads. At Native he improved data correctness with Pydantic validations and stronger negative-path tests, and at prior roles he cut long-running pipeline runtimes by 60% and unified migrating event sources while preserving analytics semantics. Comfortable both as an architect and hands-on engineer, he brings a practical background in SQL, Python, Spark/Scala, and CI/CD to ensure stable operations and faster analyst feedback loops. Based in Paraíba, Brazil, Felipe pairs formal computer science training with a continual self-driven push to deepen fundamentals—aiming to become a great computer scientist while delivering production-grade data systems.
11 years of coding experience
8 years of employment as a software developer
Advanced 2, English Language and Literature/Letters, Advanced 2, English Language and Literature/Letters at Associação Brasil América
Computer Science, Computer Science at Universidade Federal de Pernambuco
Colégio Decisão
Technical of Game Programming, Computer Games and Programming Skills, Technical of Game Programming, Computer Games and Programming Skills at Cícero Dias
Contributions:4 PRs, 22 comments, 1 issue in 2 years 11 months
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