Senior Data Architect Data Engineer 26-06256

Location: Washington DC
Duration: 6 Months (Possible Extension)

Position Overview

We are seeking a highly experienced Senior Data Architect / Data Engineer to support a large-scale data modernization initiative focused on transforming legacy data environments into modern cloud-based analytical platforms.

This role will be responsible for designing developing and optimizing enterprise data architectures scalable ETL/ELT pipelines and advanced analytics infrastructure to support economic forecasting policy research and enterprise reporting initiatives.

The ideal candidate is a hands-on technical expert with deep experience in enterprise data engineering cloud technologies workflow orchestration database architecture and large-scale data integration. This individual will collaborate closely with research teams data analysts architects and business stakeholders to improve data accessibility scalability governance and operational efficiency.

• Design develop and maintain scalable enterprise data architectures and analytical platforms
• Build and optimize robust ETL/ELT pipelines for ingesting transforming and delivering structured and unstructured data
• Develop scalable database solutions data lakes and enterprise data platforms
• Create conceptual logical and physical data models aligned with business and research objectives
• Implement data integration strategies across multiple on-premises and cloud-based systems

• Design and automate data workflows using modern orchestration tools
• Develop scalable data processing frameworks for high-volume datasets
• Optimize data flows database performance and pipeline efficiency
• Implement monitoring validation and data quality controls across all data systems

• Support migration of legacy systems and workflows to modern cloud platforms
• Implement scalable cloud-native data solutions and automation frameworks
• Collaborate on enterprise modernization and DataOps initiatives
• Assist with CI/CD implementation and deployment automation for data platforms

• Design and maintain relational and enterprise database structures
• Develop backup recovery and access security procedures
• Maintain metadata documentation data dictionaries and technical specifications
• Ensure data integrity governance and compliance standards are maintained

• Partner with economists analysts technical teams and business stakeholders
• Translate complex business requirements into scalable technical solutions
• Provide technical leadership and recommendations for future-state architecture
• Support analytics visualization and reporting initiatives

• Identify opportunities for automation and operational efficiency improvements
• Conduct root cause analysis for data and system-related issues
• Contribute to enterprise data architecture standards and best practices
• Support adoption of advanced analytics and machine learning capabilities

• Bachelors degree in Computer Science Information Technology Engineering or related technical field
• Advanced degree preferred

• Minimum 7 years of experience in Data Architecture Data Engineering or related technical roles
• Strong hands-on experience designing enterprise data platforms and data integration solutions
• Experience building and maintaining large-scale ETL/ELT pipelines
• Experience with cloud migrations and modern data infrastructure implementations

Strong experience with:

• Advanced SQL development
• Python and/or R scripting
• Relational databases including:
  • PostgreSQL
  • Microsoft SQL Server
  • MySQL
• Workflow orchestration tools such as:
  • Apache Airflow
  • Prefect
  • Dagster
• Source control platforms:
  • GitHub
  • GitLab
• Linux-based development environments
• Data modeling and database optimization
• Data quality and governance practices

Experience with one or more:

• Amazon Web Services
• Microsoft Azure
• Snowflake

• Experience working with economic financial or research datasets
• Experience with time-series data and forecasting analytics
• Experience implementing Change Data Capture (CDC) methodologies
• Experience with NoSQL or graph database technologies
• Experience with machine learning model deployment and maintenance
• Experience implementing CI/CD pipelines and DataOps practices
• Knowledge of Java Scala JavaScript or Perl
• Experience supporting enterprise analytics and visualization platforms

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