Remote Data Architect: Modernize Mainframe Data

Vytwo Technologies Inc.

Prosper (TX)

On-site

USD 90,000 - 120,000

Full time

14 days+

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Job summary

Vytwo Technologies Inc. in Minneapolis, MN is seeking a data-focused professional to translate business requirements into data models and integration specs. You will partner with stakeholders, design data mappings, and define test data strategies across environments.

The role requires experience with COBOL, CICS, DB2, JCL, MVS Utilities, CA7 scheduling, and Jira, with strong SQL skills, data analysis, and production support experience in large enterprise settings.

Qualifications

Bachelor's degree in Computer Science, Information Technology, Data Management, or related field.
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 stakeholders to understand business data needs and data consumption.
Translate requirements into logical/physical data models and mappings.
Define and implement test data strategies for various testing needs.
Design and govern reusable test data patterns and provisioning processes.
Demonstrate understanding of data modeling concepts and database design.
Analyze data flow diagrams and data dictionaries to identify dependencies.
Perform data discovery and analysis across multiple databases using SQL and related tools.
Validate data quality and reconciliation across systems.
Understand data movement patterns including real-time and batch processing.
Collaborate with architecture, development, testing, and operations teams on data initiatives.
Ensure test data solutions comply with data privacy and regulatory requirements.
Document data models, mappings, and best practices for repeatable use.