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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Migration Lead - Mid-Level - **Company:** PamTen - **Location:** United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Cloud Computing, Profiling, Customer Data Management, Extract Transform Load (ETL), Data Mapping, Data Migration, Data Profiling, Database Queries, Middleware, Intrusion Detection Systems, Operational Data Store, Cloud Services, Salesforce.Com, SAP (Applications), SQL Databases, Enterprise Data Management, Data Management - **Published:** August 15, 2026 - **Apply:** https://www2.jobdiva.com/portal/?a=rijdnwzhw0mz36cpr0zwxqcj9yt1m405eam52pzlcqh06kjpfrmqaa2uyt3eiarf&compid=0/jobs/32852377#/jobs/32852377 ## About the Role 1. 4+ years of relevant enterprise delivery experience with the ability to independently own assigned scope and contribute to design and delivery decisions. 2. Hands-on data migration experience including data profiling, source-to-target mapping, ETL or ELT, SQL or data querying, transformation rules, validation, and reconciliation. 3. Experience migrating data into Salesforce objects and relationships, with understanding of IDs, external IDs, dependencies, load sequencing, and data-loading tools. 4. Working knowledge of Salesforce data requirements supporting Service Cloud, Data Cloud, OmniStudio, and OmniScript-driven processes, including the dependencies needed for guided workflows and customer interactions. 5. Ability to identify data-quality risks, resolve mapping questions, coordinate mock conversions, and maintain clear evidence of migration completeness and accuracy. 6. Strong communication and coordination skills across business SMEs, data owners, developers, QA, architecture, and cutover teams. 7. Experience working in Agile or iterative delivery environments with cross-functional onshore and offshore teams. 8. Strong verbal and written communication skills, including the ability to explain decisions, document risks and dependencies, and collaborate directly with business and technology stakeholders. 9. Experience using enterprise-approved AI-assisted tools where appropriate, with independent validation of outputs., 1. Experience migrating data for Salesforce Energy & Utilities Cloud and/or the Salesforce Clean Energy Module in utility customer information system, clean-energy, or regulated-industry programs. 2. Data Cloud, enterprise data platforms, SAP, API, or middleware experience. 3. Salesforce Data Cloud, Administrator, Energy & Utilities Cloud, data management, ETL, or cloud certifications. ## Description The Data Migration Lead will coordinate and deliver assigned migration workstreams for the greenfield Salesforce implementation. The role will help move customer, account, service, program, clean-energy, knowledge, and operational data from legacy sources into validated target structures supporting Energy & Utilities Cloud, the Clean Energy Module, Service Cloud, Sales Cloud, Data Cloud, OmniStudio, and OmniScript-driven processes. This individual will own mapping quality, migration readiness, trial loads, reconciliation, issue resolution, and clear communication across business and technical teams., 1. Lead assigned data-migration workstreams covering discovery, profiling, mapping, cleansing, transformation, loading, validation, reconciliation, and defect resolution. 2. Define source-to-target mappings for customer, account, service, program, clean-energy, knowledge, case, and operational data supporting Energy & Utilities Cloud, the Clean Energy Module, Service Cloud, Sales Cloud, Data Cloud, and OmniStudio processes. 3. Coordinate business data owners, developers, architects, QA, and integration teams to confirm data definitions, ownership, quality expectations, and migration readiness. 4. Plan and support mock loads, trial conversions, cutover rehearsals, production migration, post-load validation, and issue remediation. 5. Maintain mapping workbooks, transformation rules, data-quality findings, reconciliation evidence, issue logs, and cutover documentation. 6. 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