ETL Lead - Data || Offshore

Zensar · Remote

Source and collection record

Last observed by our collector: 9 October 2026 at 12:32 am IST. This is not a manual review or a confirmation from the employer.

Employer requisition: 151623

Job type and experience labels are automated discovery categories. The employer determines eligibility. Original experience wording was not retained separately; check the current employer page.

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Collected role description

Core Data & ETL Skills Strong experience in ETL / ELT architecture and enterprise data migration. Hands-on experience with large-scale data migration from legacy platforms to cloud. Strong knowledge of data mapping, profiling, transformation, reconciliation, and validation. Experience designing repeatable and audit-ready ETL frameworks. Azure Data Platform Skills Azure Data Factory ADLS Gen2 Azure SQL / SQL Managed Instance SQL Server Data pipelines and staging layers Monitoring and pipeline failure handling Legacy Data Skills Experience with mainframe or HP NonStop data migration is preferred. Understanding of SQL/MP, Enscribe, COBOL copybooks, packed decimals, fixed-width files, and batch data processing. Ability to translate legacy data structures into relational/cloud-native target models. Data Quality & Reconciliation Strong experience with source-to-target reconciliation. Ability to design validation rules, exception handling, and audit reports. Experience in financial, transactional, or regulatory data validation is preferred. AI & Agile Experience Exposure to AI-assisted data migration, data profiling, or ETL generation. Experience working in Agile / Scrum / SAFe delivery models. Ability to work in sprint-based, wave-based, and evidence-driven delivery structures. The role will be responsible for defining the end-to-end data migration architecture, designing ETL pipelines, handling legacy data complexity, and ensuring record-level accuracy, auditability, and functional equivalence between legacy and modernized platforms. The TrackAll data estate includes SQL/MP tables, Enscribe flat files, COBOL-driven batch data, SSIS reporting, and COLD+ reports, with target-state modernization planned around Azure-native data services. Core Data & ETL Skills Strong experience in ETL / ELT architecture and enterprise data migration. Hands-on experience with large-scale data migration from legacy platforms to cloud. Strong knowledge of data mapping, profiling, transformation, reconciliation, and validation. Experience designing repeatable and audit-ready ETL frameworks. Azure Data Platform Skills Azure Data Factory ADLS Gen2 Azure SQL / SQL Managed Instance SQL Server Data pipelines and staging layers Monitoring and pipeline failure handling Legacy Data Skills Experience with mainframe or HP NonStop data migration is preferred. Understanding of SQL/MP, Enscribe, COBOL copybooks, packed decimals, fixed-width files, and batch data processing. Ability to translate legacy data structures into relational/cloud-native target models. Data Quality & Reconciliation Strong experience with source-to-target reconciliation. Ability to design validation rules, exception handling, and audit reports. Experience in financial, transactional, or regulatory data validation is preferred. AI & Agile Experience Exposure to AI-assisted data migration, data profiling, or ETL generation. Experience working in Agile / Scrum / SAFe delivery models. Ability to work in sprint-based, wave-based, and evidence-driven delivery structures. Core Data & ETL Skills Strong experience in ETL / ELT architecture and enterprise data migration. Hands-on experience with large-scale data migration from legacy platforms to cloud. Strong knowledge of data mapping, profiling, transformation, reconciliation, and validation. Experience designing repeatable and audit-ready ETL frameworks. Azure Data Platform Skills Azure Data Factory ADLS Gen2 Azure SQL / SQL Managed Instance SQL Server Data pipelines and staging layers Monitoring and pipeline failure handling Legacy Data Skills Experience with mainframe or HP NonStop data migration is preferred. Understanding of SQL/MP, Enscribe, COBOL copybooks, packed decimals, fixed-width files, and batch data processing. Ability to translate legacy data structures into relational/cloud-native target models. Data Quality & Reconciliation Strong experience with source-to-target reconciliation. Ability to design validation rules, exception handling, and audit reports. Experience in financial, transactional, or regulatory data validation is preferred. AI & Agile Experience Exposure to AI-assisted data migration, data profiling, or ETL generation. Experience working in Agile / Scrum / SAFe delivery models. Ability to work in sprint-based, wave-based, and evidence-driven delivery structures.

Collected experience requirement

8-10 years