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The engineer will validate complex ETL pipelines and perform large-scale data migration from legacy systems to a consolidated MySQL instance. Responsibilities include building automated reconciliation scripts to ensure data parity and verifying data integrity across APIs and backend layers.
This is a remote position.
This role is critical to Client’s backend modernization and data consolidation effort, which involves migrating and merging 30 disparate databases into a single consolidated MySQL instance. This is not a standard functional UI testing role; it is a heavy backend, data-centric QA position. The engineer will validate ETL pipelines, ensure zero data loss or corruption during migration, and automate data parity checks between legacy systems and the new architecture.
Data Validation: Write complex SQL queries to validate data extraction, transformation, and loading (ETL) from legacy SQL databases into the new consolidated MySQL instance.
Migration Parity Testing: Design and execute automated reconciliation scripts to compare millions of rows between source and target systems, ensuring data integrity and business rule alignment.
Pipeline Automation: Build and maintain automated test frameworks for data pipelines, replacing manual sampling with comprehensive automated data quality checks.
API Data Verification: Work alongside C# and Java developers to verify that the newly built APIs and Data Access Layers (DAL) are surfacing the migrated data correctly.
Defect Triage: Identify, log, and troubleshoot data drift, truncation errors, mapping failures, and performance bottlenecks.
Deep SQL Expertise: 7+ years of writing advanced SQL queries (Joins, CTEs, Window Functions, Stored Procedures) in MySQL and SQL Server.
ETL/Data Migration Testing: Proven experience testing large-scale database consolidations, data warehouse migrations, or complex ETL pipelines.
Test Automation: Hands-on experience building automated data validation scripts using Python, C#, or specialized data testing tools (e.g., Great Expectations, dbt tests, QuerySurge).
Backend Mindset: Strong understanding of database schemas, primary/foreign key relationships, indexing, and data mapping documents.
Parity Discipline: Proves data equivalence through automated reconciliation, not just manual spot-checking.
API Testing Experience: Familiarity with Postman, REST Assured, or equivalent tools to test data payloads at the API level.
Code Reading Skills: Ability to read C# or Java code to understand how the Data Access Layer is transforming data.
Cloud & DevOps: Experience with Azure/AWS data services and CI/CD pipelines for automated test execution.
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