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ERP Data Integration Engineer (QAD)

IT

$ 90000.00 - $ 125000.00
Posted 09/04/2026
Permanent/Direct Hire
Permanent/Direct Hire
Job ID: 27580

Job Description

An iMPact Business Group client is seeking to hire an ERP Data Integration Engineer (QAD).  This role will have a combination of Data Mapping, ETL, and BI Reporting as it's focus.  This role is with a highly successful manufacturing client in the precision manufactured components industry.

This role will focus on -  

ERP and Custom System Data Mapping -

  • Document and map ERP data structures - tables, fields, relationships, and embedded business logic - across QAD, Progress OpenEdge, and other source systems.
  • Serve as the subject matter expert on "what does this field/table actually mean" for source ERP systems, filling a critical knowledge gap between raw data and reporting.
  • Translate business reporting requirements into accurate data models and query logic.
  • Reverse-engineer schemas and data relationships in current systems with limited or outdated documentation.
  • Produce and maintain source-to-target mapping documents for each extracted table/field, capturing transformation logic and business rules.
  • Build and maintain a living data dictionary for QAD/Progress OpenEdge (and other source systems as needed), documenting field definitions, valid values, and business meaning so this knowledge is captured as a durable asset rather than tribal knowledge.


ETL / BI Reporting Support -

  • Partner closely with the Data Lake, Alteryx, and Power BI development teams to ensure extracted data is structurally sound, semantically correct, and reporting-ready.
  • Design ETL feeds with the Data Lake as the intended target - feeding raw and curated lake layers (OCI Object Storage / Oracle ADB) - rather than building one-off, point-to-point extracts for individual reports.
  • Build and support interfaces using database integrations, ODBC connections, and file-based transfers as needed to support extraction work.
  • Troubleshoot Data Quality and mapping issues and implement corrective actions to maintain data integrity.
  • Monitor Data Flows and proactively identify opportunities for process optimization.
  • Opportunity to contribute to on-premise LLM integration work (e.g., connecting ERP/Data Lake content to locally hosted models) for internal AI-assisted data mapping, documentation, and query tooling.


Data Management & Governance -

  • Ensure data accuracy, consistency, and synchronization across enterprise systems.
  • Develop validation, reconciliation, and exception-handling processes.

Job Requirements

  • Bachelor's degree preferred, an equivalent combination of education and experience may be considered
  • 5+ years of experience in Data Engineering related to ERP system integration and BI reporting
  • 3+ years supporting Data requirements in Manufacturing organizations
  • Hands-on experience with QAD and Progress OpenEdge, including reading/interpreting Progress OpenEdge 4GL data structures and business logic used in legacy systems
  • Experience mapping, documenting, and reverse-engineering ERP data structures with experience building data mapping documents and/or data dictionaries
  • Strong SQL skills for querying, troubleshooting, and reverse-engineering unfamiliar or undocumented schemas
  • Experience reading and interpreting ERP data dictionaries, table relationships, and business logic embedded in legacy systems (ie. Progress OpenEdge 4GL structures).
  • Ability to translate business reporting requirements into accurate source-system queries.


Preferred items -

  • Experience with one or more additional major ERP platforms, such as SAP S/4HANA, SAP ECC, Oracle ERP, Microsoft Dynamics 365, Infor LN, Plex, or Epicor
  • Familiarity with Alteryx and/or Power BI, or other reporting/ETL platforms
  • Experience with SOAP services, DevOps, CI/CD pipelines, and source control systems
  • Experience with on-premise/self-hosted LLM deployments (e.g., Ollama, Open WebUI) or integrating internal data sources with locally hosted AI models

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