Virtusa
Architect (Level: Manager)
CREQ228752 Requisition # 14+ years of experience in IT 12+ years of Data Engineering, Data Modeling, Data Warehousing, Master Data Management Reference Data Management, Data Lineage, Data Governance and Meta Data Management experience required 10+ years of experience in defining Data Analytics architecture implementing multiple large volume projects across on Prem and on cloud environments. Preferably AWS cloud. 7+ years of experience collaborating with Agile teams preferred Expertise in designing, validating, and implementing multiple projects across the hybrid infrastructure Oncloud to OnPremises and vice versa Expertise in setting up Data Lakes and analytical environments Expertise with Data EngineeringBig data tools such as Python, PySpark, Kafka APIs, Talend and BODS etc. with relational SQL and NoSQL databases Experience in building data pipelines, data ingestions, data integrations, data preparations, and traditional Data warehouses and Datamarts Experience in building processes supporting data transformation, data structures, metadata, dependency and workload management Strong experience with data modelling techniques utilizing tools such as Erwin, ER Studio etc. Experience with visualization tools such as QlikView, Qlik Sense, Tableau, etc. Experience in message queuing, stream processing, and highly scalable big data data stores Meet with Senior MidLevel Management to align business process initiatives and strategies with current and planned Penske Data Engineering Analytics Architecture Evaluate Data Engineering Analytics ToolsTechniques Approaches and determine impact on strategic objectives and manage overall implementation Be the primary contact and technical lead for multiple critical programs and integrations and resolve customer issues in a timely man Mandatory Skills Data Engineering, Data Modeling, Data Warehousing, Master Data Management, Reference Data Management, Data Lineage, Data Governance and Meta Data Management Data & Analytics architecture Data EngineeringBig data tools such as Python, PySpark, Kafka, APIs, Talend and BODS, etc
CREQ228752 Requisition # 14+ years of experience in IT 12+ years of Data Engineering, Data Modeling, Data Warehousing, Master Data Management Reference Data Management, Data Lineage, Data Governance and Meta Data Management experience required 10+ years of experience in defining Data Analytics architecture implementing multiple large volume projects across on Prem and on cloud environments. Preferably AWS cloud. 7+ years of experience collaborating with Agile teams preferred Expertise in designing, validating, and implementing multiple projects across the hybrid infrastructure Oncloud to OnPremises and vice versa Expertise in setting up Data Lakes and analytical environments Expertise with Data EngineeringBig data tools such as Python, PySpark, Kafka APIs, Talend and BODS etc. with relational SQL and NoSQL databases Experience in building data pipelines, data ingestions, data integrations, data preparations, and traditional Data warehouses and Datamarts Experience in building processes supporting data transformation, data structures, metadata, dependency and workload management Strong experience with data modelling techniques utilizing tools such as Erwin, ER Studio etc. Experience with visualization tools such as QlikView, Qlik Sense, Tableau, etc. Experience in message queuing, stream processing, and highly scalable big data data stores Meet with Senior MidLevel Management to align business process initiatives and strategies with current and planned Penske Data Engineering Analytics Architecture Evaluate Data Engineering Analytics ToolsTechniques Approaches and determine impact on strategic objectives and manage overall implementation Be the primary contact and technical lead for multiple critical programs and integrations and resolve customer issues in a timely man Mandatory Skills Data Engineering, Data Modeling, Data Warehousing, Master Data Management, Reference Data Management, Data Lineage, Data Governance and Meta Data Management Data & Analytics architecture Data EngineeringBig data tools such as Python, PySpark, Kafka, APIs, Talend and BODS, etc