Data Architect — Mainframe & Test Data Strategy (Remote)

Vytwo

Prosper (TX)

On-site

USD 90,000 - 130,000

Full time

14 days+

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Benefits offered by this job

Flexible work from home

Job summary

Vytwo is seeking a data-centric professional to lead data modeling, test data management, and data quality initiatives. The role requires strong mainframe and relational database experience, with emphasis on COBOL, CICS, DB2, SQL, and data governance.

You will partner with stakeholders, architects, and engineers to design data approaches, implement test data strategies, and ensure compliant data provisioning across environments. Flexible remote work is available.

Qualifications

Bachelor's degree 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 into clear data requirements, mappings, and test data needs.
Experience working in Agile delivery environments across cross-functional teams.

Responsibilities

Partner with stakeholders to understand data needs, source systems, mappings, and data consumption.
Translate requirements into logical and physical data models and data integration specs.
Define and implement test data strategies for functional, regression, integration, and performance testing.
Design reusable test data patterns, provisioning approaches, masking, synthetic data, and environment refreshes.
Understand data modeling principles: entities, attributes, relationships, keys, indexes, and constraints.
Read and analyze ER diagrams, data dictionaries, and end-to-end data flow diagrams to identify dependencies.
Perform data discovery, analysis, and mining using SQL, Easytrieve, and related tools.
Validate data quality, integrity, consistency, and accuracy across systems.
Develop understanding of real-time and batch data movement, APIs, queues, and data pipelines.
Collaborate with architecture, development, testing, and operations to support data analysis and modernization.
Ensure test data solutions comply with privacy, retention, and regulatory requirements.