Sr Mainframe Developer / Engineer

Vytwo is hiring a Sr Mainframe Developer / Engineer for a hybrid role in Dallas, TX. This position emphasizes strong banking context and deep experience across mainframe development, data modeling, and test data management, with flexible work from home options available.

What you’ll do

• Work with business stakeholders, Product Owners, SMEs, analysts, and development teams to understand business processes, data requirements, source systems, mappings, and data consumption needs.
• Translate business rules and processes into logical and physical data models, source-to-target mappings, and data integration specifications.
• Define and implement test data strategies for functional, regression, integration, performance, automation, and modernization testing.
• Design and govern reusable test data patterns, including provisioning approaches, data masking strategies, synthetic data solutions, and environment refresh processes.
• Apply data modeling principles covering entities, attributes, relationships, schemas, primary and foreign keys, indexes, constraints, and database design standards.
• Read and analyze ERDs, database schemas, data dictionaries, and end-to-end data flow diagrams to identify dependencies and business impact.
• Perform data discovery and mining across databases, tables, files, and source systems using SQL, Easytrieve, and other query and extraction tools.
• Validate data quality, integrity, consistency, and accuracy by reviewing relationships, transformation logic, reconciliation outcomes, and business rules.
• Support data movement and integration patterns across real-time and batch processing, including event-driven architectures, APIs, messaging queues, data pipelines, and file-based interfaces.
• Partner with architecture, development, testing, and operational teams on data analysis, problem resolution, impact assessments, test automation enablement, and modernization initiatives.
• Ensure test data solutions meet data privacy, protection, retention, classification, and regulatory requirements for sensitive customer and financial information.
• Document data models, test data design patterns, source-to-target mappings, provisioning processes, and standards so solutions can be reused across enterprise efforts.

What you bring

• Banking experience is a must
• 10+ years experience is a must
• Strong mainframe and database skills, including COBOL, CICS, DB2, DB2 utilities, SQL, JCL, MVS utilities, and production support
• Experience using the CA7 scheduling tool
• Ability to analyze the as-is and design the to-be, using Jira
• Bachelor’s degree in Computer Science, Information Technology, Data Management, Engineering, or a related field (or equivalent practical experience)
• Proven experience in data analysis, data architecture, database design, test data management, quality engineering, or software delivery
• Ability to write and optimize SQL queries for discovery, validation, reconciliation, and troubleshooting
• Experience analyzing relational databases, mainframe data structures, files, batch jobs, APIs, and downstream data consumers
• Strong communication skills, including explaining complex data concepts to technical and non-technical stakeholders
• Experience collaborating in Agile delivery environments across product, engineering, quality, architecture, and operations teams

Technologies

• COBOL, CICS, DB2, SQL, JCL, MVS Utilities
• CA7, Jira, Easytrieve, SPUFI
• DB2 utilities, SQL Server, Oracle, PostgreSQL

Benefits

• Flexible work from home options available

Preferred

• Banking domain knowledge (payments, credit card, deposits, lending, or customer/account data)
• Strong experience across data analysis, data architecture, database design, and test data management
• Experience writing and optimizing SQL for data discovery, validation, reconciliation, and troubleshooting
• Experience analyzing relational databases, mainframe data structures, files, batch jobs, APIs, and downstream data consumers
• Understanding of core banking platforms, transaction processing flows, customer/account hierarchies, and regulatory reporting requirements
• Ability to trace and map data across upstream and downstream applications, databases, files, APIs, and enterprise data platforms
• Familiarity with batch and real-time processing architectures and data movement across interconnected banking systems
• Preference for enterprise test data management platform experience, including data masking, synthetic data generation, data subsetting, and automated data provisioning
• Understanding of data governance, data classification, retention, and regulations for storage, transmission, and protection of sensitive customer and financial data