Data Architect

Responsibilities

• Partner with business stakeholders, Product Owners, SMEs, analysts, and development teams to understand business processes, data requirements, source systems, data mappings, and data consumption needs.
• Translate business requirements, processes, and rules into logical and physical data models, source-to-target mappings, and data integration specifications.
• Define and implement test data strategies that support functional, regression, integration, performance, automation, and modernization testing needs.
• Design and govern reusable test data patterns, test data provisioning approaches, masking strategies, synthetic data solutions, and environment refresh processes.
• Demonstrate strong understanding of data modeling principles, including entities, attributes, relationships, schemas, primary and foreign keys, indexes, constraints, and overall database design.
• Read, interpret, and analyze Entity Relationship Diagrams, database schemas, data dictionaries, and end-to-end data flow diagrams to identify data dependencies and business impact.
• Perform data discovery, analysis, and data mining across multiple databases, tables, files, and source systems using SQL, Easytrieve, and other data query and extraction tools.
• Validate data quality, integrity, consistency, and accuracy by analyzing data relationships, transformation logic, reconciliation results, and business rules across systems.
• Develop an understanding of data movement and integration patterns, including real-time and batch processing, event-driven architectures, APIs, messaging queues, data pipelines, and file-based interfaces.
• Collaborate with architecture, development, testing, and operational teams to support data analysis, problem resolution, impact assessments, test automation enablement, and system modernization initiatives.
• Ensure test data solutions comply with data privacy, data protection, retention, classification, and regulatory requirements for sensitive customer and financial data.
• Document data models, test data design patterns, source-to-target mappings, provisioning processes, standards, and best practices for repeatable enterprise use.

Requirements

• Bachelor's degree in Computer Science, Information Technology, Data Management, Engineering, or a related field, or equivalent practical experience.
• Strong experience in data analysis, data architecture, database design, test data management, quality engineering, or software delivery.
• Proficiency writing and optimizing SQL queries for data discovery, validation, reconciliation, and troubleshooting.
• Experience analyzing relational databases, mainframe data structures, files, batch jobs, APIs, and downstream data consumers.
• Ability to translate business rules and system behavior into clear data requirements, mappings, and test data needs.
• Strong communication skills with the ability to explain complex data concepts to technical and non-technical stakeholders.
• Experience working in Agile delivery environments and collaborating across product, engineering, quality, architecture, and operations teams.

Core Competencies

Demonstrates expertise in data analysis, data architecture, and database design, with a strong focus on test data management and quality engineering. Proficient in translating business requirements into data models and ensuring compliance with data privacy and regulatory standards.

Tools & Technologies

• SQL
• Easytrieve
• APIs
• Messaging Queues
• Batch Jobs