[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-cloud-data-engineering-im-bereich-snowflake-azure":3,"similar-cloud-data-engineering-im-bereich-snowflake-azure":38},{"id":4,"slug":5,"title":6,"skills":7,"budget":24,"duration":24,"location":25,"onsitePercent":26,"contractType":27,"foundAt":28,"category":29,"description":33,"rawText":34,"language":35,"projectId":36,"sourceUrl":37},1782,"cloud-data-engineering-im-bereich-snowflake-azure","Cloud Data Engineering im Bereich Snowflake \u002F Azure",[8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23],"Snowflake","dbt","Data Vault 2.0","Azure Data Factory","Microsoft Fabric","OneLake","Delta Lake","PySpark","Power BI","Git","Azure DevOps","CI\u002FCD","Azure Data Lake Storage Gen2","Terraform","SAP ECC","S\u002F4HANA",null,"München",50,"contracting","2026-05-12T13:25:42+00:00",{"id":30,"slug":31,"label":32},4,"data_analytics","Data & Analytics","Konzeption und Umsetzung von ETL\u002FELT-Prozessen mit Snowflake und dbt. Entwicklung skalierbarer Datenarchitektur mit Data Vault 2.0 für SAP-Integration. Evaluierung von Microsoft Fabric und Entwicklung von Supply-Chain-KPIs mit Power BI.","Cloud Data Engineering im Bereich Snowflake \u002F Azure\nProjektnummer: FE21-99500-M-CO\nStandort: München, Bayern\nArbeitsweise: Hybrid\nLaufzeit: Keine Angabe\nStartdatum: ab sofort\n\nProjektaufgaben:\n- Konzeption, Umsetzung und kontinuierliche Optimierung leistungsfähiger ETL- und ELT-Prozesse auf Basis von Snowflake und dbt\n\n- Entwicklung und Pflege einer skalierbaren Datenarchitektur unter Einsatz von Data Vault 2.0 zur Integration heterogener Quellsysteme (z. B. SAP ECC, S\u002F4HANA, CRM)\n\n- Extraktion, Transformation und Harmonisierung komplexer SAP-Business-Logiken in ein unternehmensweites, analytisches Datenmodell\n\n- Evaluierung und Einführung von Microsoft Fabric als innovative Plattform für Prototyping sowie Self-Service-BI-Anwendungen\n\n- Konzeption und Umsetzung von Supply-Chain-KPIs sowie die Entwicklung von Reporting- und Dashboard-Lösungen mit Power BI\n\n- Sicherstellung der Datenqualität und Bereitstellung entscheidungsrelevanter Kennzahlen zur Messung der Lieferperformance und -zuverlässigkeit\n\nProjektanforderungen:\n- Fundiertes Wissen im Umgang mit modernen Datenplattformen und Technologien wie Microsoft Fabric, Snowflake, dbt, Data Vault 2.0 sowie Azure Data Factory (ADF)\n\n- Mehrjährige Erfahrung in der Arbeit mit OneLake, Delta Lake und PySpark sowie in der Entwicklung von Reporting- und Visualisierungslösungen mit Power BI\n\n- Sicherer Umgang mit Versionsverwaltung (Git), Azure DevOps sowie der Implementierung und Pflege von CI\u002FCD-Pipelines im Entwicklungsprozess\n\n- Expertise im Cloud-basierten Datenmanagement unter Nutzung von Azure-Services, insbesondere Azure Data Lake Storage Gen2 (ADLS Gen2)\n\n- Kenntnisse in der Infrastrukturautomatisierung, idealerweise mit Terraform\n\n- Praxis in der Integration und Verarbeitung von Daten aus SAP-Systemen (ECC und S\u002F4HANA) als zentrale Quellsysteme\n\nSkills: Anwendungen, Azure, CI\u002FCD, CRM, Cloud, Datenmanagement, Datenmodell, DevOps, ETL, Entwicklung, Git, Implementierung, Integration, Optimierung, Power BI, Prototyping, Reporting, S\u002F4HANA, SAP, Service, Umsetzung, Vault, Versionsverwaltung\n\nAnsprechpartner:\nEva Schade\nProfessional Recruiting\nFERCHAU Contract GmbH, Niederlassung München CONTRACT\nClaudius-Keller-Straße 3a\n81669 München\n+49 89 95468-158\neic-contract@ferchau.com","de","FE21-99500-M-CO","https:\u002F\u002Ftouch.ferchau.com\u002Fde\u002Fde\u002Fprojekt\u002F505120",{"items":39},[40,55,75,91,105],{"id":41,"slug":42,"title":43,"skills":44,"budget":49,"duration":50,"location":51,"onsitePercent":52,"contractType":27,"foundAt":53,"category":54},4900,"product-manager-data-analytics","Product Manager Data & Analytics",[32,45,46,47,48],"Product Management","AI","Danish","English","Negotiable","6 Monate mit Verlängerungsmöglichkeit","Copenhagen",60,"2026-05-20T15:45:28+00:00",{"id":30,"slug":31,"label":32},{"id":56,"slug":57,"title":58,"skills":59,"budget":24,"duration":71,"location":72,"onsitePercent":24,"contractType":27,"foundAt":73,"category":74},4835,"data-solution-architect-delivery-lead-mfd","Data \u002F Solution Architect (Delivery Lead) (m\u002Ff\u002Fd)",[60,61,62,63,64,65,66,67,68,69,70],"Data Architecture","Solution Architecture","Treasury","MS SQL Server","SSAS","Databricks","Microsoft Azure","Data Modeling","Kimball","Lakehouse","Stakeholder Management","Start: 06\u002F26","Vienna","2026-05-20T13:21:14+00:00",{"id":30,"slug":31,"label":32},{"id":76,"slug":77,"title":78,"skills":79,"budget":24,"duration":24,"location":72,"onsitePercent":24,"contractType":27,"foundAt":89,"category":90},4834,"data-governance-data-quality-engineer-mfd","Data Governance & Data Quality Engineer (m\u002Ff\u002Fd)",[80,81,82,83,84,85,86,87,88],"Data governance frameworks","DAMA","GDPR","Databricks Unity Catalog","Data lineage tools","Data validation frameworks","SQL","Testing tools","Azure","2026-05-20T13:21:07+00:00",{"id":30,"slug":31,"label":32},{"id":92,"slug":93,"title":94,"skills":95,"budget":24,"duration":24,"location":24,"onsitePercent":102,"contractType":27,"foundAt":103,"category":104},4832,"data-engineer-nearshore-german-speaking-mfd","Data Engineer (Nearshore - German speaking) (m\u002Ff\u002Fd)",[86,96,97,98,99,8,100,101],"DBT","Python","Data Warehousing","ETL","Apache Airflow","Data Pipeline Orchestration",0,"2026-05-20T13:20:53+00:00",{"id":30,"slug":31,"label":32},{"id":106,"slug":107,"title":108,"skills":109,"budget":116,"duration":117,"location":118,"onsitePercent":102,"contractType":27,"foundAt":119,"category":120},4826,"100-remote-data-engineer-ms-azure-python-mwd","100% remote: Data Engineer – MS Azure \u002F Python (m\u002Fw\u002Fd)",[97,110,12,111,112,113,16,114,115],"Azure Synapse","FastAPI","Data Engineering","API-Entwicklung","Scrum","Kanban","Verhandelbar","2026 (140 Personentage)","Berlin","2026-05-20T13:05:35+00:00",{"id":30,"slug":31,"label":32}]