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Data Warehouse, Lake and Lakehouse architecture patterns. Distributed data processing using frameworks such as Spark or Flink. Designing and supporting batch and near-real-time ingestion pipelines. Building incremental, idempotent, and fault-tolerant data pipelines. Data quality, reconciliation, and
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