Senior IT Data Engineer
At a glance
Highlights
- hybrid work environment
- mission-critical initiatives
- competitive compensation and benefits
- professional growth opportunities
Heads up
- u.s. citizenship required
- federal project eligibility
- 7+ years experience required
Why this role might suit you
The position provides exposure to mission-critical federal research, opportunities to work with advanced data platforms, and a hybrid schedule in Washington, D.C., combined with competitive compensation and clear pathways for professional growth.
Skills
About the role
Senior IT Data Engineer (TO-BH-2)
Diverse Agile Solutions (DAS)
Location: Washington, D.C. (Hybrid)
Position Type: Full-Time
Citizenship Requirement: U.S. Citizen Required
Client: Federal Reserve Board – Division of Research & Statistics (R&S)
Experience Level: Senior (7+ Years)
Security Requirement: Must be eligible to work on Federal projects
About Diverse Agile Solutions (DAS)
At Diverse Agile Solutions (DAS), we deliver innovative technology solutions that help government agencies and commercial organizations modernize operations, improve decision-making, and achieve mission success. We are seeking a highly skilled Senior IT Data Engineer to support the Federal Reserve Board's Data Architecture, Technology, and Analytics (DATA) Section within the Division of Research & Statistics.
This is an exciting opportunity to contribute to the modernization of enterprise data architecture and analytics capabilities that support economic research, policy analysis, and data-driven decision-making at one of the nation’s most influential institutions.
Position Overview
The Senior IT Data Engineer will play a critical role in transforming how the Federal Reserve Board's Division of Research & Statistics ingests, organizes, processes, and visualizes data. This position is responsible for designing, developing, and optimizing enterprise data architectures, scalable data pipelines, and advanced analytics platforms that support economists, researchers, and technical teams.
The ideal candidate is a hands-on data engineering professional with deep expertise in data modeling, database architecture, ETL/ELT development, cloud technologies, and enterprise-scale data solutions. This individual will help drive next-generation data initiatives while ensuring efficient, secure, and reliable data delivery across multiple platforms and environments.
Key Responsibilities
Design, develop, and maintain enterprise data architectures, databases, and data integration solutions.
Build, optimize, and automate scalable ETL/ELT pipelines for structured and unstructured data sources.
Develop and maintain high-performance data processing frameworks supporting large-scale analytics workloads.
Design conceptual, logical, and physical data models aligned with business and research requirements.
Implement and manage data lake, data warehouse, and enterprise data platform solutions.
Collaborate with economists, researchers, and technical stakeholders to support data-driven research and policy initiatives.
Optimize data flow, storage, and processing architectures for performance, scalability, and reliability.
Perform root cause analysis on data and business processes to identify improvement opportunities.
Support migration of data pipelines and workflows between on-premises and cloud environments.
Develop and maintain DataOps practices, CI/CD pipelines, and automated deployment processes.
Ensure adherence to data governance, security, and architectural standards.
Evaluate emerging technologies and recommend innovative solutions to improve enterprise data capabilities.
Document technical solutions, architecture designs, and operational procedures.
Required Qualifications
Education
Bachelor’s degree in Computer Science, Information Technology, Engineering, Data Science, or a related technical field.
Advanced degree (Master’s or Ph.D.) preferred.
Experience
Minimum of 7 years of professional experience in Data Engineering, Data Architecture, Database Administration, or related disciplines.
Proven experience designing and implementing enterprise-scale data solutions.
Experience supporting complex research, analytics, or data-intensive environments.
Strong ability to work independently while supporting multiple stakeholders and projects.
Required Technical Skills
Data Engineering & Architecture
Advanced SQL expertise.
Extensive experience with:
PostgreSQL
Microsoft SQL Server
MySQL
Data modeling and enterprise information architecture design.
Data lake and data warehouse architecture.
Change Data Capture (CDC) implementation and maintenance.
Data integration and pipeline automation.
Programming & Analytics
Advanced proficiency in:
Python
R
Experience with additional programming languages such as:
Java
Scala
JavaScript
Perl
Data Processing & Orchestration
ETL/ELT workflow development and automation.
Distributed computing and large-scale data processing.
Workflow orchestration platforms such as:
Apache Airflow
Prefect
Dagster
AWS Step Functions
Cloud & Modern Data Platforms
Hands-on experience with:
AWS
Microsoft Azure
Snowflake
Cloud migration of data pipelines and workflows.
Enterprise data platform modernization initiatives.
DevOps & DataOps
CI/CD pipeline implementation and support.
GitLab and GitHub source control management.
Linux-based development environments.
Automated testing, deployment, and operational monitoring.
Preferred Qualifications
Experience working with economic, financial, or research-oriented data environments.
Knowledge of time-series data analysis and forecasting methodologies.
Experience with NoSQL databases and graph database technologies.
Experience developing, training, deploying, and maintaining machine learning models.
Familiarity with advanced analytics, statistical modeling, and predictive analytics.
Experience supporting Federal Government agencies or highly regulated organizations.
Desired Competencies
Exceptional analytical and problem-solving skills.
Strong troubleshooting and root-cause analysis capabilities.
Excellent written and verbal communication skills.
Ability to communicate complex technical concepts to both technical and non-technical stakeholders.
Strong customer-service mindset and collaborative approach.
Self-motivated, detail-oriented, and results-driven professional.
Why Join DAS?
Work on mission-critical initiatives supporting the Federal Reserve Board.
Collaborate with leading economists, researchers, and technology professionals.
Contribute to innovative data modernization and analytics programs.
Competitive compensation and benefits package.
Opportunities for professional growth and career advancement.
Hybrid work environment in the Washington, D.C. metropolitan area.
Apply Today
If you are a highly motivated Data Engineer with a passion for building modern, scalable data solutions and supporting impactful economic research initiatives, we encourage you to apply and join the DAS team supporting the Federal Reserve Board in Washington, D.C.
Compensation
This Data Engineer role pays $70k-$82k/yr. Within typical range for data engineer roles in United States.
Questions about this role
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