Contract Performance Period : July 15, 2026 - December 31, 2026
Job Location : Washington, DC location(s) (Metro Access) On-Site 5 days/week.
Direct Hire : Term: through 31/12/2026, with a strong possibility of extension
Pay Range : Depending on Experience
Travel Requirements : Washington, DC location(s) (Metro Access) On-Site 5 days/week.
Working Remotely : Not possible
Project Description :
Qualification Requirements :
Skills Requirements :
Responsibilities :
Job ID : 1566
Job Location : Washington, DC location(s) (Metro Access) On-Site 5 days/week.
Direct Hire : Term: through 31/12/2026, with a strong possibility of extension
Pay Range : Depending on Experience
Travel Requirements : Washington, DC location(s) (Metro Access) On-Site 5 days/week.
Working Remotely : Not possible
Project Description :
We are seeking an experienced, detail-oriented Data Architect/Engineer to expand and optimize data and data pipeline architecture, as well as optimize data flow and collection for economic policy and research teams at a large, highly regulated federal financial institution.
The ideal candidate is a 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 economists and technical experts, ensuring optimal data delivery architecture is designed and developed. The right candidate will be excited by the prospect of optimizing or re-designing an enterprise data architecture to support the next generation of data initiatives.
US Citizenship is required for this position.
Qualification Requirements :
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical field; advanced degree preferred
- At least 7 years of related data architecture/engineering experience
- Advanced working knowledge of SQL and relational database platforms (PostgreSQL, Microsoft SQL Server, MySQL)
- Advanced working knowledge of Python, R, and other scripting languages for data engineering and analytics
- Experience with large-scale data systems including distributed computing, scalable data processing, and high-volume data workload optimization
- Experience designing, developing, and automating ETL/ELT workflows and data integration pipelines
- Experience with workflow orchestration tools such as Apache Airflow, Prefect, Dagster, or AWS Step Functions
- Experience migrating workflows and data pipelines between on-premises and cloud environments
- Experience developing in Linux environments and using source control platforms (GitLab, GitHub)
- In-depth experience designing and implementing database, data lake, and enterprise data platform solutions
- Strong hands-on software engineering experience including development, testing, and deployment of data applications
- 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 with NoSQL and graph database technologies
- Experience developing, training, deploying, and maintaining machine learning models
- 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 languages such as Java, Scala, JavaScript, or Perl
- Excellent oral and written communication skills with a strong customer service orientation
Skills Requirements :
- SQL & relational databases (PostgreSQL, Microsoft SQL Server, MySQL)
- Python, R & scripting languages (Java, Scala, JavaScript, Perl)
- ETL/ELT workflow design, development & automation
- Workflow orchestration (Apache Airflow, Prefect, Dagster, AWS Step Functions)
- Distributed computing & large-scale data processing architecture
- Data lake & enterprise data platform design and implementation
- NoSQL & graph database technologies
- Cloud platforms (AWS, Microsoft Azure, Snowflake)
- Change Data Capture (CDC) & data warehouse implementation
- CI/CD pipelines & DataOps platforms
- Machine learning model development, training & deployment
- Time series data analysis & forecasting
- Source control (GitLab, GitHub) & Linux development environments
- Structured & unstructured data processing and integration
- Enterprise information architecture (conceptual, logical & physical levels)
Responsibilities :
- Expand and optimize data and data pipeline architecture to support economic policy and research teams
- Design and develop optimal data delivery architecture in collaboration with economists and technical experts
- Build, optimize, and maintain scalable databases, data pipelines, and data processing frameworks
- Design and automate ETL/ELT workflows and data integration pipelines
- Migrate workflows and data pipelines between on-premises and cloud environments
- Process, analyze, and integrate structured and unstructured data sources
- Design and communicate enterprise information architecture at conceptual, logical, and physical levels
- Implement and maintain data warehouse solutions utilizing Change Data Capture (CDC) methodologies
- Implement and maintain CI/CD pipelines and DataOps platforms
- Develop, train, deploy, and maintain machine learning models
- Perform root cause analysis on internal and external data and business processes to identify improvement opportunities
- Support the data needs of multiple teams and systems with a strong service mindset
- Document data architecture designs, pipelines, and technical processes
Job ID : 1566
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