Data Architect

Reporter Newspapers; United States; Hybrid; USD 138,000 - 172,000; Full time

Benefits offered by this job

Medical, Dental, Vision benefits

401k with company matching

Life insurance

Job summary

Reporter Newspapers in St. Louis, MO seeks a Research Data Architect to design modern data platforms for economic datasets, including FRED. Focus is on scalable models, governance, and secure AWS-based access, with AI integration and migration planning.

The role collaborates with cross-functional teams to optimize systems, implement data processing frameworks, and guide data access for APIs, in a hybrid on-site/work-from-home setup.

Qualifications

• 7+ years in data architecture, data engineering, or database design in enterprise cloud environments.
• AWS cloud data architecture including ingestion, processing, storage, and exposure of data.
• Expertise in data modeling, lifecycle management, integration patterns, partitioning, caching, and security (classification, access control, encryption, retention, auditability).
• Knowledge of DataOps, governance, data privacy regulations, data warehousing, big data, and AI/ML data requirements.
• Strong communication and collaboration skills to translate complex topics for varied audiences.

Responsibilities

• Define and evolve target data architecture for economic data systems.
• Design scalable storage for billions of time-series observations and historical revisions.
• Develop and standardize metadata schemas for discoverability, lineage, and governance.
• Implement scalable data processing frameworks for growing datasets.
• Improve indexing and metadata strategies to enhance search and discovery.
• Enable advanced analytical capabilities for researchers and developers.
• Partner with architects to optimize data access patterns for APIs and applications.
• Optimize current-state architecture including SQL tuning and performance.
• Design migration strategies and future-state architecture.

Skills

Data architecture

AWS cloud

Data modeling

DataOps

AI/ML data

Job description

Description

Hybrid 4 days on-site, 1 day work from home in St. Louis, MO Our client seeks a Research Data Architect to design and modernize data architecture supporting prominent research platforms, including FRED. The role will define scalable data platforms, data models, and governance to support growth, analytics, and secure global access to economic data. The architect will collaborate with application and platform teams to optimize current systems while planning future-state architecture, AI integration, and migration roadmaps in an AWS environment. Due to client requirements, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance. Rate: $100.00 to $125.00/hr. w2 JN -79

Responsibilities

• Define and evolve target data architecture for economic data systems.
• Design scalable storage for billions of time-series observations and historical revisions.
• Develop and standardize metadata schemas for discoverability, lineage, and governance.
• Implement scalable data processing frameworks for growing datasets.
• Improve indexing and metadata strategies to enhance search and discovery.
• Enable advanced analytical capabilities for researchers and developers.
• Partner with architects to optimize data access patterns for APIs and applications.
• Optimize current-state architecture including SQL tuning, indexing, and performance.
• Design future-state architecture, migration strategies, and tool recommendations.
• Support the addition of new datasets and integration of AI capabilities.

Experience Requirements

7+ years in data architecture, data engineering, or database design with enterprise cloud data implementations in regulated environments. Experience designing secure, scalable, and high-availability public-facing platforms. Cloud data architecture on AWS, including ingestion, processing, storage, and exposure of data. Expertise in data modeling, lifecycle management, integration patterns, partitioning, caching, data access patterns, and security strategies including classification, access control, encryption, retention, and auditability. Knowledge of DataOps practices, modern data stack tools, governance, SQL, data privacy regulations, data warehousing, big data, and AI/ML data requirements. Strong communication and collaboration skills with the ability to translate technical topics for varied audiences. Proven delivery of complex projects in cross-functional environments with consensus building.

Preferred

Preferred: time-series data platforms, distributed query engines, large-scale processing, data catalog and metadata platforms, research or economic datasets, and public data access experience.