Data Engineer (W2 Candidates only)

Data Engineer
Location: 100% Remote
Duration: 3 Months Contract (possible extensions)

TOP SKILLS:

• Infor CloudSuite, NetSuite, & IQMS (at least 2 of 3)
• Data Cleanse/Audit/Unification/Normalization
• SQL query

JOB DESCRIPTION:

• Data Cleansing Consultant to support a private equity-backed client in Phase 1 of their data unification initiative. The ideal candidate will have extensive experience in data cleaning, normalization, and standardization processes across multiple ERP systems.
• This individual will be responsible for transforming fragmented datasets into a cohesive structure to enable accurate and actionable reporting.
• The engagement will focus heavily on addressing discrepancies in vendor IDs, product IDs, customer IDs, and other critical data points while preparing for the subsequent implementation of a Data Cube.
• The consultant will work closely with internal teams, leveraging SQL and ETL tools, to consolidate and standardize data assets effectively.

KEY RESPONSIBILITIES:

• Data Cleaning and Normalization:
• Execute thorough data analysis to identify inconsistencies across multiple ERP systems (Infor Syteline, NetSuite, IQMS, Dynamics GP, MAS, Command Central).
• Clean and standardize data for vendor IDs, product IDs, customer IDs, and other key attributes to ensure consistency across systems.
• Create rules and processes that address discrepancies (e.g., same product with different names in different systems).
• Standardization Across Systems:
• Develop naming conventions, categorization frameworks, and tagging mechanisms for data normalization.
• Ensure data assets from legacy systems like Excel files, homegrown ERP solutions, and disconnected databases integrate seamlessly into the unified structure.
• ETL Tool Utilization:
• Work with SeeDataSync (ETL tool currently in use) to manage on-prem data extraction and transformation for reporting purposes.
• Ensure the proper migration of data to the organization's dedicated SQL server while maintaining data integrity.
• Collaboration and Stakeholder Communication:
• Partner with internal Business Systems Analysts (BSA), IT teams, and leadership to understand requirements and business goals.
• Provide actionable documentation and progress updates, enabling stakeholders to align Phase 1 deliverables with Phase 2 goals.
• Reporting Infrastructure Preparation:
• Prepare the foundation for the Data Cube implementation by ensuring clean and structured datasets that can be leveraged for slicing and dicing.