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Marcio Oliveira
Marcio Oliveira @marciohdo ·
🚀 Engenharia de dados não é só ETL e armazenamento. É entender o negócio, construir pipelines que contam histórias reais e garantir dados confiáveis para IA que transforma decisões em ouro 💡. Quem domina isso está montando o futuro. #DataEngineering #IA #CarreiraTech ☕
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MeeSum 미삼
MeeSum 미삼 @mexumsays5 ·
I’m looking for passionate data engineers to collaborate on projects, exchange expertise, and create impactful solutions while learning and growing together #dataengineering
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Pyrite
Pyrite @not_an_ai_horse ·
Startups often have a "Data Gap": Great product, but total chaos in the data architecture. 📉 My team of 4 (all 7+ YOE) is launching a firm to fix that. We bridge the gap between high-level Data Engineering and Fullstack execution. 🛠️ DM to scale!! #DataEngineering #Startups
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Abhishek Tripathi
Abhishek Tripathi @cloudandtechie ·
Day 40: Control Data Drift! 🛡️ Maintain strict data quality and flexibility in your lake by using Delta Lake Schema Enforcement to prevent data pollution and Schema Evolution to safely update table definitions as your business needs change. ⚡📉 #dataengineering #dataanalyticyn
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Moosa Kazim
Moosa Kazim @GM_MK007 ·
Day 59 of my Data Engineering journey 🚀 Today I learned error handling in Apache Airflow: • Retries & delays • Handling failures • Idempotent tasks • Fault-tolerant pipelines Failures happen. Recovery matters. Day 59 ✅ #DataEngineering #Airflow #Python #LearningInPublic
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Manjusha Jadhav
Manjusha Jadhav @Manjusha_Morey ·
🚀 Modern Data Stack with dbt Sources → Ingestion → Bronze → 🔥 dbt → Silver/Gold → BI dbt = SQL transformations + data modeling + testing + version control Flows: 🟢 Data ⚫ SQL ⚪ Code (Git + CI/CD) 🔴 Trigger 👉 Scalable ELT, faster analytics #DataEngineering #dbt #svvhqk
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