Location: REMOTE
Description: You will play a lead role for helping define, build and evolve key architectural components of the data ecosystem underlying the core platform.
Responsibilities
• Define the modern distributed data store architecture and design leveraging a hybrid cloud environment, distributed data pipelines, and incorporating automated governance
• Research, evaluate and select tools (marketplace and in-house) to meet the metadata capture and management needs of modern data architectures deployed at scale
• Develop and implement data domain (DDD based) modeling, data engineering, data replication and data resiliency design standards for autonomy, agility and scale
• Define integration patterns for real-time events and change data capture
• Act in the role of lead design authority to include: breaking down business requirements into technical tasks, establishing design and coding standards, code reviews, etc.
• Define Data Operations strategy and operating model for Data Anonymization, Synthetic Data Generation and Test Data Management
• Define and deliver innovative Enterprise Data Services to realize the data capabilities that are core to data strategy
• Ensure that data management rigor is in place so that users are confident in the quality of the data • Guide agile teams in applying these patterns to key software products and autonomous application architectures
• Collaborate with and influences solution architects, engineers & delivery teams to adopt enterprise data architecture specifications in products
Qualifications:
• 10+ years hand-on experience in Enterprise Data Architecture, Data Management and Data Strategy
• Deep experience with large scale, complex enterprise systems in a high availability, high volume, performant and distributed environment.
• Strong analytical and quantitative skills with the ability to use data and metrics to justify requirements, features and demonstrate business value
• Deep expertise in Data Management capabilities involving architecture, modeling (physical and logical), data governance, storage, resilience, security and replication
• Prior experience in data integration, interoperability, metadata management and data quality solutions
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