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Mainframe Data Conversion Lead (Hybrid)

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S R INTERNATIONAL INC

Remote

$145,600 Salary, Full-Time

Posted 3 days ago (Updated 2 hours ago) • Actively hiring

Expires 6/13/2026

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Job Description

Mainframe Data Conversion Lead (Hybrid)
S R INTERNATIONAL INC
Phoenix, AZ Job Details Full-time $65•$75 an hour 14 hours ago Qualifications Data model design Performance tuning Data modeling Data Integration (Data management) Data migration DB2 Salesforce Mainframe COBOL APIs Informatica Cross-functional collaboration Project leadership Cross-functional team management T-SQL Full Job Description This Position is for Local Arizona residents only.
Job Title:
Mainframe Data Conversion Lead Job ID:
10977•(Hybrid)
Client:
State of Arizona•AZDES•
DTS Closing Date & Time:
5/13/2026@ 4 PM This is a Hybrid position and expected to be in office once a week. Local candidates only. 10+ years of overall data integration / ETL experience with at least 5+ years specifically in Mainframe to Modern Platform data migrations.
Required Skills:
Previous experience in Mainframe data conversion (This must be on Resume) Salesforce Expert Informatica Expert SQL Server Expert 10+ years of overall data integration / ETL experience with at least 5+ years specifically in Mainframe to Modern Platform data migrations. Strong experience migrating data from IBM Mainframe environments (z/OS, DB2, VSAM, IMS, COBOL, JCL). Expert-level hands-on experience with Informatica Intelligent Cloud Services (IICS). Strong proficiency in SQL Server development (T-SQL, stored procedures, performance tuning). Solid experience with Salesforce data migration (Salesforce objects, Data Loader, Bulk API, Salesforce Connect, External Objects). Deep understanding of data modeling, normalization, hierarchical vs relational data structures, and mainframe-to-relational conversion techniques. Experience in large-scale Data Conversion / Legacy Modernization projects (highly preferred). Strong knowledge of data quality frameworks and tools. Excellent analytical, problem-solving, and communication skills. Ability to work independently and lead cross-functional teams. Preferred Skills Informatica Data Quality (IDQ)
MuleSoft Salesforce Service Cloud Job Descriptions:
We are seeking an experienced Mainframe Data Conversion Lead to lead the complex migration of legacy mainframe data (primarily IBM z/OS, DB2, VSAM, IMS, and COBOL-based systems ) into Salesforce using Informatica as the primary ETL tool and SQL Server as the staging and transformation platform. The ideal candidate will have deep expertise in mainframe data structures, data mapping, cleansing, transformation, and loading into Salesforce (Service Cloud, and custom objects) . This role is critical in ensuring data accuracy, integrity, and compliance during large-scale data conversion initiatives.
Key Responsibilities:
Lead end-to-end mainframe data conversion projects from discovery through go-live and hypercare. Analyze and document mainframe data structures including DB2 tables, VSAM files, IMS databases, flat files, and COBOL copybooks. Design and develop data mapping documents, source-to-target mappings, and transformation rules from mainframe sources to Salesforce objects. Build, optimize, and maintain robust ETL processes using Informatica PowerCenter / IICS for extraction, cleansing, transformation, and loading. Use SQL Server (stored procedures, SSIS, SQL scripts) as an intermediate staging, cleansing, and reconciliation platform. Work closely with Salesforce architects and developers to ensure data is loaded efficiently using Salesforce APIs, Bulk API, and Data Loader (or Informatica Salesforce Connector). Perform data profiling, data quality assessment, cleansing, deduplication, and enrichment. Develop and execute data validation, reconciliation, and cutover plans with business and technical teams. Mentor junior team members. Establish and enforce data conversion best practices, standards, and governance. Provide regular status reporting to project management and stakeholders on data conversion progress, risks, and issues.

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