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John Hancock is looking to define and implement enterprise-wide processes to consume and streamline test data provisioning, test data masking, automation, and environment set up tasks to transform data for use by the quality engineering team.

Requirements

• At least 8+ year IT industry experience
• 6 years of experience in data management and architecting data systems
• Current with modern data engineering principles, frameworks, and design patterns in a Cloud environment – Azure preferred
• Expertise in data masking, synthetic data generation and subsetting techniques
• AI driven data strategies
• Experience with data modelling
• Working knowledge with various python libraries/frameworks such as NumPy, Pandas, Matplotlib, PyTorch, Tensorflow, Keras

Responsibilities

• Design and Implement test data Management frameworks and solutions
• Develop strategies for synthetic data generation, data masking etc.
• Define and Enforce data Governance and access Controls for test environment.
• Understand the overall design and structure of data landscape in the organization.
• Implement processes for data integration.
• Implement processes to consume test data in lower environments
• Architect reusable frameworks to adopt data masking and data provisioning

Other

• Bachelors in a Data Science/Data Architect field
• At least 8+ year IT industry experience
• Must have solid understanding of Test automation framework and Test strategies
• Certifications are highly desired but not an absolute must have.
• 3 days in office, 2 days from Home; Remote working option is not available.