Senior IT Data Engineer

Diverse Agile Solutions•Washington, DC

4d•Onsite

About The Position

Diverse Agile Solutions is seeking a highly experienced Senior IT Data Engineer to support the Federal Reserve Board's Division of Research & Statistics (R&S) within the Data Architecture, Technology, and Analytics (DATA) organization. This individual will play a critical role in transforming how enterprise data is ingested, modeled, organized, processed, and delivered across research and economic policy teams. The ideal candidate combines deep technical expertise in data engineering, enterprise data architecture, and cloud technologies with a passion for building scalable, high-performance data platforms. This position requires an experienced professional who enjoys designing modern data architectures, optimizing complex data pipelines, and enabling advanced analytics for mission-critical research initiatives.

Requirements

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical discipline.
Minimum of 7 years of professional experience in Data Engineering, Data Architecture, or related disciplines.
Advanced knowledge of SQL and relational database platforms including: PostgreSQL Microsoft SQL Server MySQL
Advanced programming experience with: Python R Data engineering scripting languages
Extensive experience designing scalable data architectures.
Strong experience developing ETL/ELT pipelines.
Experience building enterprise data integration solutions.
Experience with workflow orchestration technologies including: Apache Airflow Prefect Dagster AWS Step Functions
Experience processing structured and unstructured datasets.
Experience with Linux development environments.
Experience using GitLab and/or GitHub source control.
Strong understanding of enterprise information architecture principles.
Excellent analytical, troubleshooting, and problem-solving skills.
Outstanding written and verbal communication skills.
Ability to work independently while supporting multiple technical teams.

Nice To Haves

Master's degree in Computer Science or related field
Experience supporting Federal Government agencies
Experience working with economic or financial data
Experience within research organizations
Experience with time-series data analysis
Experience implementing enterprise data lakes
Experience with NoSQL databases
Experience with Graph databases
Experience developing Machine Learning models
Experience implementing Change Data Capture (CDC)
Experience building enterprise Data Warehouse solutions
Experience implementing CI/CD pipelines for DataOps
Experience with Snowflake
Experience with AWS Cloud
Experience with Microsoft Azure
Experience with Java
Experience with Scala
Experience with JavaScript
Experience with Perl

Responsibilities

Design, develop, and maintain enterprise-scale data architectures supporting research and analytics initiatives.
Build and optimize scalable ETL/ELT pipelines for structured and unstructured data.
Develop high-performance data integration solutions across multiple enterprise platforms.
Design logical and physical data models supporting enterprise information architecture.
Build scalable databases, data lakes, and enterprise data platforms.
Optimize database performance and large-scale data processing environments.
Design workflow automation using orchestration platforms such as Apache Airflow, Prefect, Dagster, or AWS Step Functions.
Develop and maintain cloud-based data engineering solutions within AWS and Azure environments.
Migrate data pipelines between on-premises and cloud infrastructures.
Support economists, researchers, and technical teams with reliable, high-quality data solutions.
Perform root cause analysis of data quality issues and recommend long-term improvements.
Develop CI/CD pipelines supporting DataOps and automated deployment practices.
Collaborate with cross-functional teams to improve enterprise data governance and operational efficiency.
Design scalable data processing frameworks capable of supporting large analytical workloads.
Document enterprise data architecture, data lineage, and technical designs.
Participate in code reviews, testing, deployment, and continuous improvement activities.