Design, develop and implement modern data infrastructure and analytical capabilities to enhance economic forecasting and policymaking, with specific focus on modernizing legacy data environments. The program transforms legacy and proprietary databases, and fragmented data pipelines into integrated cloud platforms, enterprise data integration systems, and collaboration tools that improve data accessibility and security. These initiatives streamline workflows, enable timely economic insights, and support innovative analytical work. This modernization effort ensures continued leadership in economic analysis, promotes efficiency in meeting Congressional mandates, and supports adoption of advanced tools and best practices organization-wide.
The Data Architecture, Technology, and Analytics (DATA) section is tasked with transforming how the Federal Reserve Board's Division of Research & Statistics (R&S) ingests, organize, uses, and visualizes data.
The Data Architecture, Technology, and Analytics (DATA) section is looking for an experienced detailed oriented Data Architect/Engineer who will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for economic policy and research teams. The ideal candidate is an experienced hands-on data modeler with working knowledge of database design and administration, data pipeline building, and data wrangling who enjoys improving existing data systems and/or building them from the ground up. The Data Architect/Engineer will support our economists and technical experts and will ensure optimal data delivery architecture is designed and developed. They must have a service mindset, be self-directed, and be comfortable supporting the data needs of multiple teams and systems. The right candidate will be excited by the prospect of optimizing or even redesigning the R&S division's data architecture to support our next generation of data initiatives.
Requirements- Bachelor's degree in Computer Science, Information Systems, Data Science, or related field required; Master's degree preferred.
- Minimum of 7 years experience in data architecture, data modeling, database design, and data integration.
- Strong experience with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) and ETL/ELT pipelines.
- Expertise in cloud platforms such as AWS, Azure, or Google Cloud, specifically with data services.
- Proficient in data modeling tools (e.g., ERwin, PowerDesigner) and SQL.
- Familiarity with data governance frameworks, data security best practices, and compliance standards.
- Experience collaborating with cross-functional teams and communicating complex data concepts to non-technical stakeholders.
- Strong analytical, problem-solving, and organizational skills.
- Relevant certifications such as Certified Data Management Professional (CDMP) or AWS Certified Big Data - Specialty are a plus.
