Senior Mainframe & Data Solutions Engineer — Remote

Vytwo; Prosper (TX); On-site; USD 90,000 - 140,000; Full time

Benefits offered by this job

Flexible remote work

Job summary

Vytwo is seeking a data analytics-focused professional to partner with business stakeholders and engineering teams to understand data requirements and design robust data models. You will define test data strategies, govern data patterns, and ensure data quality across multiple systems including mainframes via SQL and data tooling.

The role emphasizes collaboration in Agile environments, attention to data governance, and modern data integration practices within a banking context.

Qualifications

• 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.

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 ER 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.

Skills

Data analysis

Data architecture

Database design

Test data management

Quality engineering

Software delivery

SQL proficiency

Agile delivery

Communication

Education

Bachelor's degree in Computer Science/IT/Data Management/Engineering

Tools

COBOL

CICS

DB2

DB2 utilities

SQL

JCL

MVS Utilities

CA7 Scheduling

Jira

Easytrieve

SPUFI

VSAM

Job description

Vytwo is seeking a data analytics-focused professional to partner with business stakeholders and engineering teams to understand data requirements and design robust data models. You will define test data strategies, govern data patterns, and ensure data quality across multiple systems including mainframes via SQL and data tooling.

The role emphasizes collaboration in Agile environments, attention to data governance, and modern data integration practices within a banking context.