What are the responsibilities and job description for the Test Data Architect position at Argyllinfotech?
Role: Test Data Architect
Location: MN (on-site 3 days)
Client: US Bank (Through CTS)
The Test Data Architect is responsible for defining, designing, and governing enterprise test data strategies that support application testing, modernization, automation, and software delivery across complex environments.
The role requires strong experience in enterprise data architecture, data modeling, database design, data analysis, test data management, data quality, integration patterns, and SQL. The person will work closely with business, product, architecture, development, testing, and operations teams.
Key Responsibilities
Understand business processes, data requirements, source systems, and downstream data consumption.
Translate business requirements and rules into logical and physical data models, source-to-target mappings, and integration specifications.
Define enterprise test data strategies supporting functional, regression, integration, performance, automation, and modernization testing.
Design reusable test data patterns including data provisioning, data masking, synthetic data, and environment refresh.
Understand and analyze ER diagrams, schemas, data dictionaries, data flows, entities, attributes, relationships, primary/foreign keys, indexes, and constraints.
Perform data discovery, analysis, profiling, and data mining across databases, files, mainframe systems, and other sources.
Validate data quality, integrity, consistency, reconciliation, transformation logic, and business rules.
Understand enterprise integration patterns including batch processing, real-time/event-driven architecture, APIs, messaging queues, data pipelines, and file-based interfaces.
Support data privacy, protection, retention, classification, and regulatory requirements, particularly for sensitive customer and financial data.
Document data models, mappings, test data patterns, provisioning processes, standards, and reusable best practices.
Collaborate across architecture, engineering, QA, operations, product, and business teams.
Key Skill Set
Core Data Skills: Data Architecture • Data Modeling • Logical & Physical Data Models • Database Design • ERD Analysis • Source-to-Target Mapping • Data Lineage • Data Discovery • Data Profiling • Data Quality • Data Reconciliation
Test Data: Test Data Management • Test Data Strategy • Data Provisioning • Data Masking • Synthetic Data • Environment Refresh • Functional Testing • Regression Testing • Integration Testing • Performance Testing • Test Automation
Integration: APIs • Batch Processing • Event-Driven Architecture • Messaging Queues • Data Pipelines • File-Based Interfaces • Downstream Data Consumers
Databases: DB2 • SQL Server • Oracle • PostgreSQL
Query / Mainframe: SQL • Easytrieve • SPUFI • COBOL (basic understanding) • JCL (basic understanding) • VSAM datasets • Mainframe data structures • Batch jobs
Governance & Security: Data Privacy • Data Protection • Data Retention • Data Classification • Regulatory Compliance • Sensitive Customer and Financial Data
Business / Leadership: Business Requirements • Data Requirements • Stakeholder Management • Cross-functional Collaboration • Agile Delivery • Translating business rules into technical data requirements • Communicating complex data concepts to technical and non-technical audiences
Most Important Skills for the Interview:
I would prioritize Data Architecture Data Modeling SQL Test Data Management Mainframe Data Data Quality/Reconciliation Integration Patterns.
The posting specifically says the interviews will be highly technical, so I would expect scenario-based questions such as designing test data for a complex banking system, tracing data from DB2/mainframe through APIs into downstream systems, explaining logical vs. physical models, writing SQL for reconciliation, designing masking/synthetic-data approaches, and troubleshooting data mismatches across systems.