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Foundations of Analytics Engineer Role: Skills, Scope, and Modern Practices - Juan Manuel Perafan

Feb 27, 2026
Juan Manuel Perafan, analytics engineer and co-author of Fundamentals of Analytics Engineering, shares his journey from psychology to shaping modern data modeling. He discusses the rise of analytics engineering, bridging business and technical teams, dbt and competing tools, Python as the glue, and testing/CI practices to stop silent data failures.
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INSIGHT

Analytics Engineering Is Business Modeling With Engineering Rigor

  • Analytics engineering equals transforming business reality into analyzable data while applying software engineering rigor.
  • The difference from past warehouse work is not the what but the how: emphasis on testing, reproducibility, and safety over speed.
INSIGHT

Data Modeling Is Librarian Work And Stakeholder Mediation

  • Modeling messy, merged systems is largely a business and librarian task, not just technical ETL.
  • Juan says unifying client tables after acquisitions demands stakeholder mediation and deep domain understanding to create a single clean source of truth.
ADVICE

Master SQL Then Practice With A Modern Warehouse

  • Learn SQL deeply and at least one modern warehouse (Databricks, Snowflake, BigQuery) because most transformations run there.
  • Complement SQL with dbt for engineering practices and use DuckDB locally for lightweight development and CI tests.
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