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The Data Migration Engineer is responsible for designing and executing the migration of historical data from legacy enterprise systems to a modern Azure SQL-based platform. Working under the guidance of the Data Engineering Lead, this role focuses on developing transformation logic, executing migration activities, validating data quality, and supporting reconciliation and production cutover to ensure a successful implementation. Key Responsibilities Develop and maintain Azure SQL scripts to extract, transform, and load (ETL) data into the target platform. Design and implement data transformation logic to align legacy data structures with the target Azure SQL data model. Collaborate with stakeholders to validate migrated data through reconciliation, ensuring completeness, consistency, and accuracy between source and target systems. Execute mock migration cycles, perform data validation, and resolve issues prior to production cutover. Document data mappings, transformation rules, reconciliation procedures, and migration assumptions to support operational readiness and knowledge transfer. Manage migration scripts using Azure DevOps, following version control, code review, and CI/CD best practices. Support data validation activities during System Integration Testing (SIT), User Acceptance Testing (UAT), and production deployment. Troubleshoot migration issues, identify data anomalies, and implement corrective actions to ensure high- quality migration outcomes. Required Skills & Experience 47 years of experience in data engineering, ETL development, or enterprise data migration projects. Strong SQL expertise, including complex query writing, stored procedures, data transformation, and performance optimization. Hands-on experience with Azure SQL Database or other cloud-based relational database platforms. Solid understanding of ETL processes, data migration methodologies, and data integration best practices. Experience performing data reconciliation and validating source-to-target data accuracy. Familiarity with Azure DevOps, Git, CI/CD pipelines, and version-controlled database scripts. Experience using AI-assisted development tools for SQL generation, data mapping, and transformation activities. Strong written and verbal communication skills with the ability to collaborate effectively in cross- functional teams. Preferred Experience Experience migrating data from legacy enterprise systems or ERP platforms. Familiarity with enterprise cloud applications and their data models. Experience with Azure Data Lake, Azure Synapse Analytics, or similar cloud data platforms. Exposure to production cutover, data validation, and reconciliation processes. Work Location: In person .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.