A detailed reference architecture for building an aviation data lakehouse on Snowflake using QAR (Quick Access Recorder) flight telemetry data. The pipeline follows a Medallion architecture (Bronze → Silver → Gold), processing HDF5-encoded flight recorder files through Snowpark Python stored procedures for decoding and resampling heterogeneous sensor signals, loading them into Snowflake-managed Apache Iceberg tables, and aggregating analytics-ready features via containerized PySpark jobs on Snowpark Container Services. Key topics include signal resampling trade-offs (4 Hz canonical rate), open lakehouse interoperability via Snowflake's Horizon Iceberg REST Catalog, fan-out parallelism with ASYNC stored procedures, and data governance controls for sensitive pilot data. Business use cases covered include predictive maintenance, fuel optimization, evidence-based training, and digital twin scenarios.
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