Data Architect

The Federal Reserve

Confirmed live 2 days ago High trust

Quick summary

Work type
On-site
Location
St. Louis, MOCleveland, OHPhiladelphia, PAChicago, ILSan Francisco, CABoston, MANew York, NYRichmond, VAAtlanta, GAMinneapolis, MNKansas City, MODallas, TX
Salary
$140,000–$170,000 / yr
Posted
11 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $177k
This role $155k
$118k most similar roles pay here $236k

This role pays less than 64% of similar roles. Most pay $142,400–$211,625 — the shaded band above. At the midpoint, this role pays about $155k versus about $177k 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 23 open roles on FindRole.

Listed pay typically runs $133,350–$174,450 across 16 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 powering economic data platforms, such as FRED, which manage massive collections of time-series data, historical revisions, and archival documents. The role involves designing scalable storage architectures, developing metadata schemas for discoverability, and implementing processing frameworks to support growing volumes. You will partner with the Application Architect to optimize data access patterns for APIs while ensuring robust security and governance. Key technical requirements include expertise in PostgreSQL—specifically schema design, indexing, and partitioning—alongside experience with AWS cloud platforms, DataOps, and distributed query engines. The position requires proficiency in data modeling, lifecycle management, and integration patterns to ensure reliable data flow. This role solves the challenge of providing scalable, secure access to complex economic datasets for researchers and developers through advanced analytics and infrastructure.

What you'll do

  • Design and evolve the target data architecture supporting economic data systems.
  • Create scalable storage architectures capable of supporting billions of time-series observations and historical revisions.
  • Develop metadata schemas to improve dataset discoverability, lineage, and governance across multiple platforms.
  • Implement scalable data processing frameworks to handle growing volumes of large-scale datasets.
  • Optimize indexing and metadata strategies to enhance search and discovery for researchers and developers.
  • Partner with the Application Architect to optimize data access patterns for APIs and applications.
  • Establish robust security strategies including data classification, encryption, and compliance with privacy regulations.

What we're looking for

  • 7-10+ years of experience in data architecture, data engineering, or database design in complex, regulated environments.
  • Experience with large-scale enterprise cloud data implementations and modern technology stacks, preferably using AWS.
  • Demonstrated experience designing and supporting scalable, secure, and high-performing public-facing applications.
  • Knowledge of DataOps, data governance, SQL, and relevant data privacy regulations.
  • Expert knowledge of data modeling techniques, lifecycle management, and integration patterns.
  • Expertise in data storage technologies, partitioning strategies, caching, and robust security protocols for data classification and encryption.
  • Strong hands-on experience with PostgreSQL, including schema design, indexing, and high-availability configurations for large-scale time-series data.
  • Proven ability to lead complex projects in cross-functional environments and communicate technical risks to executive leadership.

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