Maven Companies Inc.
Senior Data Modeler/Architect (Erwin, Retail, SCM)
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Modeler/Architect with a long-term contract, requiring 14+ years of IT experience, expertise in Erwin, SQL, Oracle, and retail/SCM data systems. Skills in Big Data and PySpark/Spark are advantageous.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
Unknown
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ποΈ - Date
May 16, 2026
π - Duration
Unknown
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ποΈ - Location
Unknown
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π - Contract
Unknown
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π - Security
Unknown
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π - Location detailed
United States
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π§ - Skills detailed
#Data Engineering #Data Warehouse #ERWin #PySpark #Oracle #Metadata #Spark (Apache Spark) #Physical Data Model #Conceptual Data Model #SQL (Structured Query Language)
Role description
Senior Data Modeler/Architect
Job Type-Long Term Contract
Must have at least 14+ years of IT Experience
β’ Erwin, Data Warehouse, Retail, SCM, SQL, Oracle and any Data Engineering experience Bigdata, Pyspark/Spark is a plus
β’ Analyzing and translating business needs into long-term solution data models.
β’ Evaluating existing data systems.
β’ Working with the development team to create conceptual data models and data flows.
β’ Developing best practices for data coding to ensure consistency within the system.
β’ Reviewing modifications of existing systems for cross-compatibility.
β’ Implementing data strategies and developing physical data models.
β’ Updating and optimizing local and metadata models.
β’ Evaluating implemented data systems for variances, discrepancies, and efficiency.
β’ Troubleshooting and optimizing data systems.
Senior Data Modeler/Architect
Job Type-Long Term Contract
Must have at least 14+ years of IT Experience
β’ Erwin, Data Warehouse, Retail, SCM, SQL, Oracle and any Data Engineering experience Bigdata, Pyspark/Spark is a plus
β’ Analyzing and translating business needs into long-term solution data models.
β’ Evaluating existing data systems.
β’ Working with the development team to create conceptual data models and data flows.
β’ Developing best practices for data coding to ensure consistency within the system.
β’ Reviewing modifications of existing systems for cross-compatibility.
β’ Implementing data strategies and developing physical data models.
β’ Updating and optimizing local and metadata models.
β’ Evaluating implemented data systems for variances, discrepancies, and efficiency.
β’ Troubleshooting and optimizing data systems.
