Data Architect

The Federal Reserve

Quick summary

Work type
On-site
Location
St. Louis, MOPhiladelphia, PAChicago, ILSan Francisco, CANew York, NY
Posted
2 days ago
Nearby
95 roles within 25 mi

Market check

Salary context

How this pay compares to similar roles

Similar $172k
$125k most similar roles pay here $219k

This listing doesn't post a salary. Most similar roles pay $133,900–$210,112.

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 34 open roles on FindRole.

Listed pay typically runs $136,550–$185,200 across 28 roles with salary data.

Most-posted roles

View all roles at The Federal Reserve

At a glance

TL;DR · Data Architect

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The Data Architect at the Federal Reserve Bank of St. Louis will lead the technical vision and modernization of data architecture for global economic research platforms like FRED, managing massive datasets used by millions worldwide. This role involves designing scalable storage architectures, developing metadata schemas, and implementing data processing frameworks to support long-term growth and advanced analytics. The Data Architect will collaborate closely with Application/Enterprise Architects to ensure seamless integration between data platforms and application services. Required qualifications include 7+ years of experience in large-scale enterprise cloud data implementations, expertise in modern data technology stacks like AWS, and a deep understanding of data governance, security, and privacy regulations. Preferred skills encompass time-series data platforms, distributed query engines, and familiarity with economic datasets or research environments.

Skills

AWS DataOps SQL CI/CD Terraform Kubernetes Docker PostgreSQL Snowflake Apache Hadoop Apache Spark Elasticsearch AI/ML Data Governance Data Privacy Regulations Data Warehousing Big Data Technologies

What you'll do

  • Define and evolve the target data architecture supporting economic data systems.
  • Design scalable storage architectures for billions of time-series observations and historical revisions.
  • Develop metadata schemas to enhance dataset discoverability, lineage, and governance.
  • Standardize dataset structures and metadata across multiple platforms.
  • Implement scalable data processing frameworks to support growing dataset volumes.

What we're looking for

  • 7+ years of experience in data architecture and large-scale enterprise cloud implementations.
  • Deep understanding of modern data technology stacks, cloud platforms (AWS preferred), and enterprise software solutions.
  • Proven expertise in designing scalable storage architectures for billions of time-series observations.
  • Demonstrated knowledge of data governance, metadata schemas, and dataset standardization across platforms.
  • Experience implementing robust security strategies including encryption, access control, and auditability.
  • Outstanding communication skills to translate technical topics into business terms for various audiences.

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