Data Architect

The Federal Reserve

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Boston, MANew York, NYPhiladelphia, PACleveland, OHRichmond, VAAtlanta, GAChicago, ILSt. Louis, MOMinneapolis, MNKansas City, MODallas, TXSan Francisco, CA
Salary
$140,000–$170,000 / yr
Employment
Full-time
Posted
39 days ago
Freshness
Confirmed live today

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $182k
This role $155k
$127k $235k
below market most similar roles pay here above market

This role pays less than 70% of similar roles. Most pay $149,820–$215,125 — the blue band above. At the midpoint, this role pays about $155k versus about $182k for comparable roles.

Based on 240 similar postings.

Employer

About The Federal Reserve

The Federal Reserve is the central bank of the United States—one of the world's most influential, trusted and prestigious financial organizations.

The Federal Reserve currently has 33 open roles on FindRole.

Listed pay typically runs $113,250–$158,300 across 12 roles with salary data.

Most-posted roles

View all roles at The Federal Reserve

At a glance

TL;DR · Data Architect

The Data Architect will lead the design and modernization of data architecture for economic data platforms, such as FRED, at the Federal Reserve Bank of St. Louis. This role involves designing scalable storage architectures, data models, and governance frameworks to manage massive collections of economic time-series data, historical revisions, and archival documents. The architect will develop metadata schemas, implement data processing frameworks, and optimize data access patterns for APIs. Key technical requirements include expertise in AWS cloud platforms, SQL, DataOps, and data privacy regulations. The position requires hands-on experience with PostgreSQL for schema design, indexing, and partitioning. The architect must address the technical challenge of ensuring consistent, reliable, and secure data flows for public-facing research applications while supporting advanced analytics and global access to economic datasets.

What you'll do

  • Define and evolve the target data architecture for economic data systems.
  • Design scalable storage architectures for billions of time-series observations and historical revisions.
  • Develop metadata schemas to support dataset discoverability, lineage, and governance.
  • Standardize dataset structures and metadata across multiple platforms.
  • Implement scalable data processing frameworks to handle growing dataset volumes.
  • Improve indexing and metadata strategies to support dataset search and discovery.
  • Optimize data access patterns for APIs and applications in partnership with the Application Architect.
  • Design standardized approaches for data classification, access control, encryption, and auditability.

What we're looking for

  • 7-10+ years of experience in data architecture, data engineering, or database design in complex, highly regulated environments.
  • Deep understanding of modern data technology stacks, cloud data platforms (AWS preferred), and enterprise software solutions.
  • Demonstrated experience designing and supporting scalable, secure, and high-performance public-facing applications.
  • Knowledge of DataOps, data governance, SQL, data privacy regulations, and modern data stack tools.
  • Expert knowledge of data modeling, lifecycle management, and integration patterns for consistent and reusable data flows.
  • Strong hands-on experience with PostgreSQL, including schema design, indexing, partitioning, and high-availability configurations.
  • Ability to communicate technical topics and risks to both technologists and executive leadership.
  • Experience with time-series data, distributed query engines, or data catalog platforms (preferred).

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