SAP HANA (ERP Data Domain Lead/architect - Sales) :: New jersey city (NJ) onsite

Talentmovers Inc
Jersey City, NJ, United States
about 2 months ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
$100,000.0 - $200,000.0
Working hours
Regular working hours

Tech stack

Information Engineering Data Governance Data Integration Extract Transform Load (ETL) Data Mapping Metadata SAP (Applications) SAP HANA SQL Databases Transaction Data Enterprise Data Management Google Cloud
+4 more
Data Lakes People Soft Data Management Domain Model

Job description

Mandatory Skill :: ERP, Data Modeling, GCP, SQL, Manufacturing, Data Lake, Sales We are seeking an experienced ERP Data Domain Lead to own the Sales domain model across SAP, PeopleSoft, and associated enterprise systems. This role will define and maintain the canonical data model for sales-related data in the datalake, ensuring consistent definitions, high-quality data, and alignment with reporting and analytics needs. Responsibilities:

  • Define the canonical data model for Sales domain entities such as customer, prospect, quote, order, invoice, shipment, returns, pricing, and sales hierarchy.
  • Map SAP and PeopleSoft source objects to standardized business concepts.
  • Partner with Sales, Finance, Operations, Data Engineering, and BI teams to align business definitions.
  • Establish data standards, naming conventions, metadata, lineage, and data quality rules.
  • Support source-to-target mapping, data harmonization, and issue resolution.
  • Ensure the model supports analytics, reporting, master data, and downstream data products., Position Overview We are seeking highly skilled Senior SAP Syniti Consultants to join Bridge Atlantic. The ideal candidate will have extensive experience in data integration, ETL…
  • 1 month ago +

Requirements

  • Strong experience in enterprise data modeling, ideally in ERP environments.
  • Strong experience of SAP and/or PeopleSoft sales or order-to-cash processes.
  • Strong understanding of sales master data, transactional data, and reporting structures.
  • Experience working with data lake, lakehouse, or modern analytics platforms.

Ability to translate business requirements into logical and physical data models.

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