Key skills
JavaScriptPythonJavaScalaSQLNoSQLRPerlMachine LearningETLELTData WarehousingAnalyticsSnowflakeAirflowApache AirflowAWSAzurePostgreSQLMySQLSQL ServerGitHubGitLabCI/CDCommunicationCollaboration
About this role
Job Title: Data Architect
Location: Washington, DC
Duration: 12+ Months
Job Type: Contract
Interview: Phone/Video + Possible In-Person Interview
Job Description
The Federal Reserve Board is seeking an experienced Data Architect to support the modernization of enterprise data infrastructure and analytical capabilities. The selected candidate will play a key role in designing scalable data platforms, modernizing legacy systems, building enterprise data pipelines, and enabling advanced analytics that support economic forecasting and policymaking.
The ideal candidate is a hands-on Data Architect/Engineer with expertise in data modeling, database architecture, ETL/ELT development, cloud technologies, and enterprise data platforms. This role requires close collaboration with economists, researchers, and technical teams to design secure, scalable, and high-performing data solutions.
Required Skills
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- Minimum 7+ years of experience as a Data Architect or Data Engineer.
- Advanced SQL expertise with PostgreSQL, Microsoft SQL Server, and MySQL.
- Strong programming experience with Python and R.
- Experience designing logical, conceptual, and physical data models.
- Expertise building scalable ETL/ELT pipelines.
- Experience with workflow orchestration tools:
- Apache Airflow
- Prefect
- Dagster
- AWS Step Functions
- Strong experience with:
- Data Lakes
- Enterprise Data Platforms
- Distributed Data Systems
- Data Warehousing
- Experience migrating workloads between on-premises and cloud environments.
- Experience processing structured and unstructured data.
- Hands-on Linux development experience.
- Experience using GitHub and/or GitLab.
- Strong understanding of enterprise information architecture.
- Experience implementing:
- Change Data Capture (CDC)
- CI/CD Pipelines
- DataOps
- Experience with NoSQL and Graph databases.
- Experience with cloud technologies:
- AWS
- Microsoft Azure
- Snowflake
- Knowledge of Java, Scala, JavaScript, or Perl is a plus.
- Excellent analytical, communication, and problem-solving skills.
Roles & Responsibilities
- Analyze existing data architectures, source systems, and business processes to identify modernization opportunities.
- Design, develop, and optimize enterprise data architectures and data integration solutions.
- Build and maintain scalable ETL/ELT pipelines supporting enterprise analytics.
- Design robust data pipelines that ingest, transform, and deliver data from multiple sources.
- Develop conceptual, logical, and physical data models.
- Architect enterprise database structures, security models, backup, and recovery strategies.
- Develop and maintain metadata, data dictionaries, and technical documentation.
- Implement enterprise data quality monitoring and governance processes.
- Collaborate with research, analytics, and business teams to improve data accessibility and reporting capabilities.
- Optimize database performance and data processing frameworks.
- Automate manual processes and improve scalability through DataOps and Infrastructure automation.
- Support cloud migration initiatives and modernization projects.
- Participate in establishing enterprise data architecture standards, principles, and best practices.
- Perform root cause analysis on data issues and recommend scalable solutions.
Preferred Skills
- Experience with economic, financial, or research data.
- Understanding of time-series data and forecasting techniques.
- Experience building and deploying Machine Learning models.
- Experience working within Federal or highly regulated environments.
- Advanced knowledge of enterprise data governance and analytics platforms.
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