Data Migration Engineer - Que To Prism Modernization

Role & responsibilities

Job Title: Data Migration Engineer Que to Prism Modernization

Experience Level: 5–10 Years

Department: Data Engineering / IT Modernization

Project Scope: Legacy System (Que) to Modern Platform (Prism) Migration

Role Overview

We are seeking a highly skilled Data Migration Engineer with 5 to 7 years of experience to lead the end-to-end data transition from our legacy application (Que) to our modern platform (Prism). In this critical modernization role, you will architect, execute, and validate the migration of complex legacy datasets while ensuring zero data loss. You will leverage AI-assisted Development Life Cycle (AI DLC) tools to accelerate the writing of robust data migration scripts. The ideal candidate possesses deep expertise in data management, backup and recovery strategies, and rigorous pre- and post-migration reconciliation to identify and resolve any missing data elements.

Key Responsibilities

• End-to-End Migration Strategy: Design and execute the complete data migration lifecycle from the legacy "Que" application to the new "Prism" architecture.
• AI-Assisted Script Development: Utilize AI DLC tools (e.g., GitHub Copilot, ChatGPT Enterprise, or proprietary GenAI coding assistants) to rapidly write, optimize, and debug complex ETL and data migration scripts.
• Backup & Disaster Recovery: Establish and manage stringent backup protocols before any migration event. Ensure robust rollback mechanisms and recovery plans are fully tested and functional.
• Data Reconciliation & Validation: Perform comprehensive pre-migration data profiling and post-migration validation. Design automated reconciliation reports to instantly identify orphaned records, truncated fields, or missing elements between Que and Prism.
• Data Mapping & Transformation: Collaborate with application architects and business stakeholders to map legacy data structures in Que to the modernized schema in Prism.
• Performance Tuning: Optimize migration queries and scripts to handle large volumes of data within tight cutover windows, minimizing system downtime.
• Documentation & Compliance: Maintain detailed documentation of data lineage, transformation rules, migration logs, and AI-generated script audits for compliance and historical tracking.

Required Skills & Competencies

Core Data & Migration Expertise

• Data Migration & ETL: 5–7 years of proven experience leading large-scale data migrations, specifically in legacy modernization projects.
• Data Reconciliation: Deep expertise in writing validation scripts to compare source and target databases, ensuring 100% data fidelity pre- and post-migration.
• Database Management: Advanced proficiency in SQL and relational database architecture. Experience working with major enterprise databases (e.g., SQL Server, PostgreSQL).
• Backup & Recovery: Strong practical knowledge of database backup mechanisms, state-point restores, and creating fail-safe rollback procedures.

AI & Automation Skills

• AI DLC Integration: Demonstrated experience using AI coding assistants to write, document, and test data migration scripts (Python, SQL, Bash).
• Scripting & Programming: Proficiency in Python, shell scripting, or similar languages for automating extraction, transformation, and load processes.

Analytical & Problem-Solving

• Data Profiling: Ability to deeply analyze legacy data in "Que" to identify anomalies, bad formatting, or historical corruption prior to moving it to "Prism".
• Troubleshooting: Rapid identification and resolution of bottlenecks, data drops, or schema mismatches during dry runs and live cutovers.
• Communication: Strong ability to translate complex data mappings and migration risks to non-technical project managers and business leaders.