We are seeking a skilled Data Migration Engineer to lead and execute end-to-end data migration initiatives from legacy systems to modern platforms.
The ideal candidate will have hands-on experience in ETL pipelines , data engineering , and data validation , with strong proficiency in Python and SQL .
You will be responsible for ensuring the accuracy, completeness, and integrity of data throughout the migration lifecycle, while minimizing disruption to business operations.
Key Responsibilities
1.
Migration Planning and Analysis
- Analyze legacy data structures, formats, and dependencies.
- Profile source data to identify quality issues and inconsistencies.
- Work closely with business and technical stakeholders to define migration scope, timelines, and cutover/rollback strategies.
- Translate business requirements into migration plans and technical specifications.
2.
ETL Development and Execution
- Design, develop, and maintain scalable ETL pipelines for data extraction, transformation, and loading.
- Cleanse, map, and transform data to align with the schema and constraints of the target system.
- Execute both incremental and full data loads with minimal downtime.
- Ensure data consistency, referential integrity, and format alignment during migration.
3.
Validation, Testing, and Reconciliation
- Conduct trial runs and dry migrations to validate data accuracy and completeness.
- Develop and perform data reconciliation between source and target systems to ensure parity.
- Implement robust error-handling , logging , and rollback mechanisms .
- Investigate and resolve discrepancies or failed loads.
4.
Performance Tuning and Optimization
- Monitor performance of data migration tasks and troubleshoot bottlenecks.
- Tune queries, scripts, and pipelines to support large-volume data transfers efficiently.
- Ensure compliance with data governance , privacy , and security policies throughout the migration.
Requirements:
Requirements
- 3-8 years of relevant experience
- Strong experience in data migration , ETL processes , and data engineering practices.
- Proficient in Python and SQL for scripting, transformation, and automation.
- Experience with data validation, reconciliation, and quality assurance
- Hands-on with data profiling tools
- Experience working with relational databases (e.g., MySQL, PostgreSQL, MS SQL Server, Oracle).
- Possess good understanding of object-oriented concepts, design patterns, concurrency and software techniques.
- Experience in application integration, monitoring and control with exposure in automated tests
- Proficient in Web services, API technologies and concepts
- Ability to manage multiple migration projects under tight timelines with high attention to detail.
- Strong analytical and problem-solving skills.
- Proficient in consuming data from a variety of sources and connecting frontend applications to backend services.
- Good in analyzing requirements, creating technical specifications and using test cases and scenarios.