Data Architect

Key Responsibilities

• Define and evolve the target data architecture supporting economic data systems.
• Design scalable storage architectures capable of supporting billions of time-series observations and historical revisions.
• Develop metadata schemas supporting dataset discoverability, lineage, and governance.
• Standardize dataset structures and metadata across multiple platforms.
• Implement scalable data processing frameworks capable of supporting growing dataset volumes.
• Improve indexing and metadata strategies that support dataset search and discovery.
• Enable advanced analytical capabilities for researchers and developers.
• Partner with the Application Architect to optimize data access patterns for APIs and applications.

Required Qualifications

• 7+ years of experience in data architecture, data engineering or database design and large-scale enterprise cloud data implementations in complex, highly regulated environments.
• Deep understanding of modern data technology stacks, cloud data platforms (AWS preferred), and enterprise software solutions.
• Demonstrated experience designing, architecting and supporting external / public-facing applications with a strong emphasis on scalability, security, availability and performance for external customer-facing platforms.
• Demonstrated knowledge of and leading adoption of industry best practices in the areas of DataOps and modern data stack tools, data governance, SQL and other query tools and knowledge of data privacy regulations.
• Industry-related certifications in one or more of the above areas are desired.
• Demonstrated experience in cloud data architecture skills including designing, architecting and delivering modern cloud data platforms to ingest, process, store and expose data across the enterprise.
• Expert knowledge of data modeling techniques and tools, data lifecycle management and integration patterns to ensure that data flows are consistent, reliable and reusable across services and solutions.
• Experience with data storage technologies, partitioning strategies, caching, data access patterns, and robust security strategies enforcing privacy and regulatory requirements including designing standardized approaches for data classification, access control, encryption, retention and auditability.
• Knowledge of data warehousing concepts and tools, big data technologies, machine learning and AI data requirements.
• Outstanding communication and collaboration skills, including translating technical topics and risks into business teams.
• Ability to personalize communication to audience from technologists to executive leadership.
• Demonstrated experience in driving consensus and delivering results in a cross-functional matrix environment.

Preferred Qualifications

• Experience working with time-series data platforms or analytical datasets.
• Experience with distributed query engines and large-scale data processing systems.
• Experience with data catalog and metadata management platforms.
• Familiarity with economic datasets or research data environments.
• Experience supporting public data access or research-oriented platforms.