Sr Mainframe Developer / Engineer
Indexed description
- Banking Experience is must
- Credit Card experience is huge plus*10+ years experience is a must*Mainframe Automation experience is a plus
Need to be able to do analysis on the as-is and come up with design of the to be, Use of Jira.
- Work Locations: Dallas, TX / Denver, CO / Minneapolis, MN
Key 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.
- 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.
- Preferred Skills & Technologies Databases
- DB2
- SQL Server
- Oracle
- PostgreSQL
- SQL
- Easytrieve
- SPUFI
- Basic understanding of COBOL, JCL, and VSAM datasets
- Experience working within banking, payments, credit card, deposits, lending, or customer/account data domains.
- Understanding of core banking platforms, transaction processing flows, customer and account hierarchies, and regulatory reporting requirements.
- Ability to trace, analyze, and map data across upstream and downstream applications, databases, files, APIs, and enterprise data platforms.
- Familiarity with batch and real-time processing architectures and the movement of data across interconnected banking systems.
- Experience with enterprise test data management platforms, data masking, synthetic data generation, data subsetting, and automated data provisioning is preferred.
- Understanding of data governance, data classification, retention requirements, and regulations governing the storage, transmission, and protection of sensitive customer and financial data.
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