Data Migration Architect

Responsibilities:

• Own end-to-end data migration strategy including discovery, profiling, mapping, transformation, validation, reconciliation, mock runs, and production cutover.
• Lead data mapping from legacy systems to target data models ensuring accuracy and consistency.
• Define and implement data migration tooling strategy across ETL/ELT platforms and cloud-native services.
• Provide technical direction for building scalable, secure, and high-performance data pipelines.
• Oversee performance engineering including throughput optimization, parallelization, indexing, and partitioning.
• Guide transformation logic, data quality rules, exception handling, and reconciliation frameworks.
• Lead mock migrations, cutover planning, dress rehearsals, and production execution activities.
• Act as subject matter expert for data models, migration frameworks, and integration touchpoints.
• Ensure compliance with data governance, regulatory standards, audit requirements, and security policies.
• Collaborate with business stakeholders, SMEs, and engineering teams to define requirements and resolve issues.
• Provide leadership through design reviews, code reviews, and architecture governance.
• Advise on cloud architecture including identity management, networking, encryption, monitoring, and cost optimization.

Required Skills And Qualifications:

• Strong experience in end-to-end data migration strategy and execution.
• Expertise in ETL/ELT processes, data profiling, validation, and reconciliation.
• Advanced SQL skills with complex data extraction and transformation experience.
• Hands-on experience with cloud-based data migration and pipeline development.
• Experience leading large-scale migration projects and cross-functional teams.
• Strong understanding of data governance, security, and compliance standards.
• Experience with Agile methodologies and structured code review practices.

Preferred Qualifications:

• Experience with large-scale cloud data migration projects.
• Knowledge of modern data pipeline frameworks and distributed processing.
• Experience with reconciliation automation and data validation dashboards.
• Familiarity with high-volume transactional data migration and optimization strategies.