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JD Edwards Data & ERP Consultant
- Remote from
- LATAM
- Salary
- Undisclosed
- Department
- Data Science & Analytics
- Employment
- Contract
- Experience
- Senior
- Published
- Apply before
- 12 Dec 2026
- Listing views
- 19
- Application actions
- 0
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About this role.
JD Edwards Data & ERP Consultant
Particle41 is seeking a talented and versatile JD Edwards Data & ERP Consultant to join our innovative team. We are staffing a dedicated consultant for a large enterprise client that runs JD Edwards as its core ERP. The client needs someone who knows the JDE data model inside and out and can build reliable data pipelines around it. This is a working seat on the client team, not a short advisory project. You will work shoulder to shoulder with their ERP, IT, and business teams every day.
In This Role, You Will:
Own JDE data work: Extract, model, and transform data from JD Edwards tables (Address Book, Item Master, Sales Order, General Ledger, and related files).
Build data pipelines: Design and maintain ETL/ELT flows from JDE into the client’s data warehouse or reporting platform.
Support ERP implementation work: Lead data mapping, conversion, cleansing, and reconciliation for implementation, upgrade, or migration efforts. Support cutover planning and execution.
Enable reporting: Build clean, trusted datasets for BI dashboards and finance and operations reporting.
Protect data quality: Set up validation and reconciliation checks between JDE and downstream systems. Find and fix root causes.
Partner with the business: Work with finance, distribution, and manufacturing users to turn their questions into data requirements.
Document as you go: Keep data flows, mappings, and conversion rules clear and current for the client team.
Skills and Experience We Value:
5+ years of hands-on JD Edwards experience (EnterpriseOne and/or World). Deep knowledge of the JDE data model and table structures is required for this role.
Strong SQL on Oracle, SQL Server, or DB2 / IBM i (AS400).
Data engineering experience: ETL/ELT development, pipeline design, and data modeling.
At least one full-cycle ERP implementation, upgrade, or migration where you owned data conversion or data migration work.
Working knowledge of core JDE modules: Financials, Distribution / Logistics, and Manufacturing.
Able to work full-time during US business hours.
Clear, confident written and spoken English. Comfortable working directly with client stakeholders.
Able to work as an independent contractor.
Nice to Have
JDE technical tools: Orchestrator, Business Services (BSSV), UBEs / Report Design Aid, Table Conversion, and Form Design Aid.
Cloud data platforms: Snowflake, Azure Data Factory, Databricks, AWS (Glue, Redshift), or dbt.
BI tools: Power BI, Tableau, or OBIEE.
Python for data processing and automation.
Industry background in manufacturing, distribution, or automotive aftermarket.
Oracle JD Edwards certification.
Prior consulting or staff augmentation experience.
What Success Looks Like
First 30 days: You understand the client’s JDE footprint, key tables, and current data flows. You deliver a first pipeline or dataset fix.
First 90 days: The client team trusts your data. Reporting and conversion work runs on documented, repeatable pipelines.
Ongoing: You are the go-to person for JDE data questions on the client team.
About Particle41
Our core values of Empowering, Leadership, Innovation, Teamwork, and Excellence drive everything we do to achieve the ultimate outcomes for our clients. Empowering Leadership for Innovation in Teamwork with Excellence ( ELITE )
E – Empowering: Enabling individuals to reach their full potential.
L – Leadership: Taking initiative and guiding each other toward success.
I – Innovation: Embracing creativity and new ideas to stay ahead.
T – Teamwork: Collaborating with empathy to achieve common goals.
E – Excellence: Striving for the highest quality in everything we do.
We seek team members who embody these values and are committed to contributing to our mission. Particle41 welcomes individuals from all backgrounds who are committed to our mission and values. We provide equal employment opportunities to all employees and applicants, ensuring that hiring and employment decisions are based on merit and qualifications without discrimination based on race, color, religion, caste, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, local, or international laws. This policy applies to all aspects of employment and hiring.
We appreciate your interest and encourage applicants from these regions to apply. If you need any assistance during the application or interview process, please feel free to reach out to us at careers@particle41.com. This role is specifically for LATAM Region only.
Annual salary information is not provided for this position. Explore salary ranges for similar roles in our Salary Directory ›
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Sample interview questions
I begin by confirming the business process, source tables, keys, and transactional grain. I document relationships across tables such as Address Book, Item Master, Sales Order, and General Ledger, then build incremental extraction and transformation logic with clear lineage, validation rules, and business-friendly definitions.
I would explain the conversion scope, profiling and cleansing approach, source-to-target mapping, mock conversion cycles, reconciliation controls, and cutover plan. A strong approach includes measurable acceptance criteria, exception management, stakeholder sign-off, and post-load validation of record counts, balances, and critical business transactions.
I would use automated completeness, uniqueness, referential-integrity, and balance checks at each pipeline stage. For financial and operational data, I would reconcile source and target counts, totals, and key control fields, track exceptions, and alert owners when defined thresholds are breached.
I would facilitate a structured discovery discussion focused on the business decision, metric definition, timeframe, grain, filters, and expected reconciliation point. I would translate the outcome into documented data requirements and a prototype dataset, then validate it with users before productionizing the pipeline.
Relevant tools may include Orchestrator, Business Services, UBEs, Table Conversion, and Report Design Aid. I select tools based on integration reliability, security, data-volume needs, and operational supportability, while keeping transformations and data contracts documented for downstream engineering and business teams.
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