Application Architect - Test Data Management

Huntington Bancshares
Columbus, OH, United States
25 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours

Tech stack

Artificial Intelligence Amazon Web Services Applications Architecture Automation of Tests Microsoft Azure Big Data Databases Data Architecture Data Governance Data Integrity IBM DB2 DevOps
+21 more
Oracle (Applications) Scrum Methodology Software Architecture E2e Testing Software Engineering SQL Databases Test Data Google Cloud Test-Driven Development (TDD) Event Driven Architecture Containerization Data Lakes Kubernetes Integration Frameworks Apache Kafka Graphql Data Management Api Design Docker Mulesoft Microservices

Job description

We are seeking an experienced Test Data Management Architect to design and implement enterprise TDM capabilities supporting unit, system, integration, and end-to-end testing. This role will define the architecture, technology, processes, and provisioning model for scalable, reusable test data solutions across delivery teams. The ideal candidate has strong expertise in application architecture, data management, QA frameworks, and financial systems, with experience integrating enterprise solutions, meeting regulatory requirements, and reducing delivery friction in a fast-paced environment., * Define TDM architecture, standards, and patterns.

  • Design scalable solutions for synthetic data and test data pipelines.
  • Provide architectural and technical guidance to engineering teams and serve as a key advocate for developer adoption of enterprise Test Data Management (TDM) solutions.
  • Collaborate with Chief Data Architecture Office in support of data governance, stewardship, and metadata teams to drive appropriate controls balanced with software development utilization of test data.
  • Ensure consistency across teams and environments
  • Align architecture with enterprise data and AI strategies
  • Define and govern test data lifecycle (create, deliver, refresh, retire)
  • Design test data provisioning models and ensure consistent lifecycle and provisioning patterns across teams
  • Define approach for reusable data patterns and referential integrity, Certain positions outside our branch network may be eligible for a flexible work arrangement. We’re combining the best of both worlds: in-office and work from home. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. Remote roles will also have the opportunity to come together in our offices for moments that matter. Specific work arrangements will be provided by the hiring team.

Requirements

  • Bachelor’s Degree
  • 7+ years of total related experience, + 5+ years of strong technical design and solution leadership experience, with 3+ years of application architecture experience preferred.
  • Proven experience designing and implementing data-intensive applications in financial services or risk management domains.
  • Broad range of experience in QA frameworks, basic test methodology, test automation, test driven development, and technology project lifecycles.
  • Proven experience with test data compliance in banking or financial services and methods to safeguard data (e.g., synthetic data, masking, tokenization)
  • 5+ years Agile Scrum experience
  • Technical Skills:
  • Expertise in software architecture principles, including microservices and event-driven architectures.
  • Strong knowledge of database technologies (e.g., SQL, Oracle, DB2) and data modeling techniques.
  • Understanding of CI/CD pipelines and DevOps practices.
  • Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
  • Familiarity with API design (REST, GraphQL) and integration tools (e.g., Kafka, MuleSoft, or similar).
  • Domain Knowledge:
  • Knowledge of financial services, banking regulations (e.g., KYC, AML, SOX), and global privacy laws (e.g., GDPR, CCPA).
  • Familiarity with data governance, data quality frameworks, and data lakes.
  • Familiarity with AI/ML for generating test and synthetic data.
  • Soft Skills:
  • Excellent problem-solving and analytical skills with a focus on delivering business value.
  • Strong communication skills to articulate complex technical concepts to non-technical stakeholders.
  • Proven ability to lead cross-functional teams and manage multiple priorities in a dynamic environment.
  • Ability to build strong partnerships and to work collaboratively with all business and IT areas.

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