Senior Data Architect

Job Title: Sr. Data Architect

Location: Onsite (Some allowance for situational telework if needed.)|Washington, DC Local DMV Only
Duration: 12+ months

Interview Mode: May ask for in person interview



Job Description:

PROJECT DESCRIPTION:



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.



BACKGROUND:

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 re

designing the R&S division''s data architecture to support our next
generation of data initiatives.





REQUIREMENTS:

The candidate shall possess the knowledge and skills set forth in the Technical
Services BOA,

Section 3.5 for labor category 3.5.9 Data Architect.

The candidate shall also demonstrate the below knowledge and experience:

• Analyze data processes, applications, and source data to understand
dependencies, anomalies,

and implicit business rules that impact the division''s ability to manage data.
Review and

analyze existing data models and processes to optimize and modernize current
data

architectures.

• Design, develop, and maintain robust data pipelines that ingest, transform,
and deliver data

from multiple sources to analytics platforms, ensuring optimal performance and
data integrity

throughout the process.

• Architect and implement ETL/ELT workflows using modern data engineering tools
and

frameworks to support large-scale data processing for economic analysis.

• Create data solution designs for economic policy and research projects,
including conceptual

models, integration models, and sourcing strategies, in alignment with the
division''s research

needs and data strategy. Translate division and section requirements into
long-term

information architecture solutions.

• Define specifications and implement database structures, including logical
and physical data

models, backup and recovery procedures, and access security controls. Develop
and maintain

formal documentation of data structures, data flows, data dictionaries, and
technical

metadata.

• Collaborate with research and business teams to improve data models and data
processes that

support analytics and visualization tools, increasing data accessibility and
fostering data

driven decision making across the organization.

• Implement processes and systems to monitor data quality, ensuring production
data is

accurate, reliable, and available for end users and dependent business
processes.

• Identify, design, and implement internal process improvements, including
automation of

manual processes, optimization of data delivery, and redesign of infrastructure
to improve

scalability and performance.

• Participate in the development of future-state data architecture standards,
guidelines, and

Principles.



Specific Requirements and Skills

• Bachelor''s degree in computer science, Information Technology, Engineering or
a related

technical field and at least 7 years of related experience; advanced degree
preferred.

• Advanced working knowledge of SQL and experience working with relational
database

platforms including PostgreSQL, Microsoft SQL Server, and MySQL.

• Advanced working knowledge of Python, R, and other scripting languages used
for data

engineering and analytics.

• Experience working with large-scale data systems, including distributed
computing, scalable

data processing, data storage architecture, and optimization of high-volume
data workloads.

• Experience designing, developing, and automating ETL/ELT workflows and data
integration

pipelines.

• Experience building, optimizing, and maintaining scalable databases, data
pipelines and data

processing frameworks.

• Experience with workflow orchestration and pipeline automation tools such as
Apache

Airflow, Prefect, Dagster, or AWS Step Functions.

• Experience migrating workflows and data pipelines between on-premises and
cloud

environments.

• Experience processing, analyzing, and integrating structured and unstructured
data sources.

• Experience developing in Linux environments and using source control
platforms such as

GitLab and/or GitHub.

• Experience performing root cause analysis on internal and external data and
business

processes to answer business questions and identify opportunities for
improvement.

• Ability to design and communicate enterprise information architecture at
conceptual, logical,

and physical levels.

• In-depth experience designing and implementing database, data lake, and
enterprise data

platform solutions.

• Strong hands-on software engineering and implementation experience, including

development, testing, and deployment of data applications and services.

• Excellent oral and written communication skills with a strong customer
service orientation.

• Exceptional analytical, problem-solving, and troubleshooting skills.

• Experience with NoSQL and graph database technologies.

• Working experience with cloud technologies such as AWS, Microsoft Azure, and
Snowflake.

• Experience implementing data warehouses utilizing Change Data Capture (CDC)

methodologies.

• Experience implementing and maintaining CI/CD pipelines and DataOps
platforms.

• Working knowledge of additional programming and scripting languages such as
Java, Scala,

JavaScript, or Perl.



Additional Desirable Skills/Experience Include



• Understanding of time series data and related analytical and forecasting
techniques.

• Experience working in a research environment and/or with economic or
financial data.

• Experience developing, training, deploying, and maintaining machine learning
models