Senior IT Data Engineer
About The Position
Diverse Agile Solutions (DAS) is 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. 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.
Requirements
- Bachelor’s degree in Computer Science, Information Technology, Engineering, Data Science, or a related technical field.
- 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.
- Advanced SQL expertise.
- Extensive experience with PostgreSQL
- Extensive experience with Microsoft SQL Server
- Extensive experience with 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.
- Advanced proficiency in Python
- Advanced proficiency in R
- Experience with additional programming languages such as Java
- Experience with additional programming languages such as Scala
- Experience with additional programming languages such as JavaScript
- Experience with additional programming languages such as Perl
- ETL/ELT workflow development and automation.
- Distributed computing and large-scale data processing.
- Workflow orchestration platforms such as Apache Airflow
- Workflow orchestration platforms such as Prefect
- Workflow orchestration platforms such as Dagster
- Workflow orchestration platforms such as AWS Step Functions
- Hands-on experience with AWS
- Hands-on experience with Microsoft Azure
- Hands-on experience with Snowflake
- Cloud migration of data pipelines and workflows.
- Enterprise data platform modernization initiatives.
- CI/CD pipeline implementation and support.
- GitLab and GitHub source control management.
- Linux-based development environments.
- Automated testing, deployment, and operational monitoring.
Nice To Haves
- Advanced degree (Master’s or Ph.D.) preferred.
- 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.
- 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.
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.
Benefits
- Competitive compensation and benefits package.
- Opportunities for professional growth and career advancement.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
