Data Migration Engineer (ETL)

Role Summary:
The Data Migration Engineer builds the extraction, transformation, and load (ETL) pipeline that moves customer data from up to six CRM sources into a staging layer and then into the new ERP, implementing the matching and deduplication logic defined by the Lead Data Architect.

Key Responsibilities:

• Build CRM (multiple Salesforce instances and Pipedrive) staging ERP extraction and transformation pipelines for up to six source systems.
• Implement matching, deduplication, and survivorship logic technically, in close collaboration with the Lead Data Architect.
• Define data lineage between different CRM systems and ETL process
• Develop and execute data validation and reconciliation test plans to ensure data integrity post-migration.
• Partner with business teams during User Acceptance Testing (UAT), translating technical data validation results into clear, business-friendly reports to build trust in the migrated data.
• Leverage generative AI for creating synthetic test data, optimizing ETL scripts, and documenting pipelines.
• Produce the clean, representative test dataset required for Q4 2026 UAT entry, and finalize it for Jan 1st, 2027.
• Produce the final production migration dataset for Q1 2027 cutover and contribute to project data quality KPIs.
• Build reconciliation and exception reports to surface unresolved data issues for the Business Data Steward.
• Develop catch process for any inconsistency post day 1 live with process for notification and validation.
• Create and maintain data dictionary and glossary for all the data transformations

Required Qualifications Experience:

• Strong SQL and ETL development background ( possibly with Alteryx).
• Experience in performance tuning of ETL pipelines and large-scale database operations.
• Strong Salesforce data model, SFDC API, and multi-instance Salesforce migration experience
• Prior experience on at least one CRM-to-ERP or multi-source data migration project.
• Practical, hands-on experience implementing fuzzy-matching or deduplication logic.
• Familiarity with the target ERPs customer master data model.

Nice to Have:

• Experience in automotive, franchise, or multi-tier distribution data structures.
• Scripting experience (Python) for custom matching/transformation logic.

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