Data Migration Engineer

Kavi Software Technologies; Chennai District; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Kavi Software Technologies is seeking a Data Migration Engineer to design and execute enterprise data migrations from legacy systems to an Azure SQL platform. The role focuses on developing ETL processes, implementing data transformation logic, and validating data quality.

You will support production cutover, run mock migrations, document mappings, and collaborate with cross‑functional teams to ensure a successful migration delivery.

Qualifications

• 4-7 years experience in Data Engineering, ETL Development, or Data Migration.
• Strong expertise in SQL, including complex queries and performance tuning.
• Hands-on with Azure SQL Database or cloud relational databases.
• Knowledge of ETL processes and data migration methodologies.
• Experience in data reconciliation and source-to-target verification.
• Familiarity with Azure DevOps, Git, and CI/CD pipelines.

Responsibilities

• Develop and maintain SQL scripts for ETL into Azure SQL.
• Design transformation logic mapping legacy data to target model.
• Perform data reconciliation to ensure accuracy and completeness.
• Execute mock migrations, validate migrated data, and resolve issues.
• Document data mappings, rules, and migration assumptions.
• Manage migration scripts using Azure DevOps, Git, CI/CD.
• Support SIT/UAT and production cutover activities.
• Troubleshoot migration issues and collaborate cross-functionally.

Skills

Data Engineering

ETL Development

Data Migration

SQL

Azure SQL

ETL Processes

Data Reconciliation

Azure DevOps

Git

CI/CD pipelines

Analytics & Troubleshooting

Tools

Azure DevOps

Git

CI/CD pipelines

Azure SQL Database

Job description

Role Summary

We are seeking a Data Migration Engineer to design and execute enterprise data migration from legacy systems to a modern Azure SQL platform. The role involves developing ETL processes, implementing data transformation logic, validating data quality, and supporting production cutover to ensure accurate and successful migration.

Key Responsibilities

• Develop and maintain SQL scripts for extracting, transforming, and loading (ETL) data into Azure SQL.
• Design data transformation logic to map legacy data structures to the target Azure SQL data model.
• Perform data reconciliation to ensure accuracy, completeness, and consistency between source and target systems.
• Execute mock migration cycles, validate migrated data, and resolve migration issues before production deployment.
• Document data mappings, transformation rules, reconciliation processes, and migration assumptions.
• Manage migration scripts using Azure DevOps, Git, and CI/CD best practices.
• Support data validation during System Integration Testing (SIT), User Acceptance Testing (UAT), and production cutover.
• Troubleshoot migration issues, identify data anomalies, and implement corrective actions.
• Collaborate with cross-functional teams to ensure successful migration delivery.

Required Skills

• 4- 7 years of experience in Data Engineering, ETL Development, or Data Migration.
• Strong expertise in SQL, including complex queries, stored procedures, data transformation, and performance optimization.
• Hands‑on experience with Azure SQL Database or other cloud‑based relational databases.
• Solid understanding of ETL processes, data migration methodologies, and data integration best practices.
• Experience in data reconciliation, validation, and source‑to‑target data verification.
• Hands‑on experience with Azure DevOps, Git, and CI/CD pipelines.
• Familiarity with AI‑assisted development tools for SQL generation, data mapping, and transformation.
• Strong analytical, troubleshooting, documentation, and communication skills.

Preferred Skills

• Experience migrating data from legacy enterprise systems or ERP platforms.
• Knowledge of Azure Data Lake, Azure Synapse Analytics, or similar cloud data platforms.
• Familiarity with enterprise cloud application data models.
• Experience supporting production cutover, reconciliation, and post‑migration validation.