Dynamics 365 CRM Data Migration Consultant

AppWorks Hub

$110K — $130K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Strong experience in data migration projects, particularly from legacy systems to Dynamics CRM.
  • Basic understanding of mainframe systems (COBOL, VSAM, DB2).
  • Hands-on experience in extracting data from mainframes to SQL databases.
  • Proficiency in Microsoft Dynamics 365 CRM data migration processes.
  • Strong SQL skills for data transformation and validation.
  • Familiarity with ETL tools like SSIS or Azure Data Factory.
  • Proficient in data cleansing, mapping, and reconciliation techniques.
  • Excellent communication skills for client-facing roles.

Responsibilities

  • Analyze legacy mainframe data and identify migration requirements.
  • Extract data from mainframes to SQL Server or staging databases.
  • Cleanse, transform, and map data for Dynamics 365 CRM migration.
  • Design and implement ETL processes using suitable migration tools.
  • Validate data accuracy for successful migration to Dynamics CRM.
  • Collaborate with business users to understand data needs.
  • Provide migration planning, timelines, and risk strategies.
  • Troubleshoot migration issues to enhance performance.
  • Document migration processes and validation results.
  • Participate in client meetings, providing status updates.

Benefits

  • Customer-facing role with potential for building client relationships.
  • Opportunity to work with cutting-edge Microsoft technologies.
  • Hands-on experience with diverse data migration tools and techniques.
  • Support a high-profile client in the New York area.
  • Flexible working arrangement based in New Jersey.
Full Job Description
Data Migration Consultant (Mainframe to Dynamics 365 CRM)
Role Overview

We are seeking an experienced Data Migration Consultant with strong expertise in migrating legacy mainframe data to Microsoft Dynamics 365 CRM. The ideal candidate should have hands-on experience extracting data from mainframe systems into SQL databases and transforming it for Dynamics CRM implementation. This role is customer-facing and requires strong communication skills and the ability to work closely with stakeholders. The position is based in New Jersey, supporting a client located in New York.

Key Responsibilities
  • Analyze legacy mainframe data structures and identify migration requirements.
  • Extract data from mainframe systems and load into SQL Server or staging databases.
  • Cleanse, transform, and map data for migration into Microsoft Dynamics 365 CRM.
  • Design and implement ETL processes using appropriate migration tools and scripts.
  • Validate data accuracy and ensure successful migration into Dynamics CRM.
  • Work closely with business users to understand data requirements and validation criteria.
  • Provide migration planning, timelines, and risk mitigation strategies.
  • Troubleshoot migration issues and optimize data migration performance.
  • Document migration processes, mapping documents, and data validation results.
  • Participate in client meetings and provide regular status updates.

Required Skills & Qualifications
  • Strong experience in data migration projects, especially legacy system to Dynamics CRM.
  • Basic understanding of Mainframe systems (COBOL files, VSAM, DB2, etc.).
  • Hands-on experience extracting data from mainframe systems into SQL databases.
  • Experience with Microsoft Dynamics 365 CRM data migration.
  • Strong SQL skills including data transformation and validation.
  • Experience with ETL tools such as SSIS, Azure Data Factory, or similar.
  • Knowledge of data cleansing, mapping, and reconciliation techniques.
  • Excellent communication and customer-facing skills.
  • Ability to work independently and manage migration timelines.

Preferred Qualifications
  • Experience with public sector or large enterprise migrations.
  • Experience with Azure integration tools and Power Platform.
  • Microsoft Dynamics or Azure certifications.
  • Experience with data governance and data quality frameworks.

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