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

Talentmovers Inc
Jersey City, United States of America
8 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 200K

Job location

Jersey City, United States of America

Tech stack

Information Engineering
Data Governance
Data Integration
ETL
Data Mapping
Metadata
SAP Applications
SAP HANA
SQL Databases
Transaction Data
Enterprise Data Management
Google Cloud Platform
Data Lake
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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