Senior IT Data Engineer

Edgewater Federal Solutions•Washington, DC

5d•Onsite

About The Position

The Data Architecture, Technology, and Analytics (DATA) section is tasked with transforming how the Federal Reserve Board’s Division of Research & Statistics (R&S) ingests, organize, uses, and visualizes data. The Data Architecture, Technology, and Analytics (DATA) section is looking for an experienced detailed oriented Data Architect/Engineer who will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for economic policy and research teams. The ideal candidate is an experienced 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 our economists and technical experts and will ensure optimal data delivery architecture is designed and developed. They must have a service mindset, be self-directed, and be comfortable supporting the data needs of multiple teams and systems. The right candidate will be excited by the prospect of optimizing or even re-designing the R&S division’s data architecture to support our next generation of data initiatives. The Senior IT Data Engineer is responsible for designing, building, and optimizing scalable data architectures, integration pipelines, and enterprise data platforms that support analytics, reporting, and operational decision-making. This role partners with business stakeholders, analysts, and technical teams to ensure data is accessible, reliable, secure, and structured to meet organizational needs. The ideal candidate brings deep hands-on expertise in data engineering, strong knowledge of database technologies, and the ability to translate complex data requirements into high-performing technical solutions.

Requirements

Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related technical field; advanced degree preferred.
Typically requires 7+ years of experience in data engineering, data architecture, or a related technical role.
Advanced proficiency in SQL and experience with relational database platforms such as PostgreSQL, Microsoft SQL Server, and MySQL.
Strong hands-on experience with Python and familiarity with additional scripting or programming languages such as R, Java, Scala, or JavaScript.
Experience designing and supporting large-scale data platforms, including data warehouses, data lakes, and enterprise information architecture.
Demonstrated expertise in ETL/ELT design, workflow orchestration, and pipeline automation tools such as Apache Airflow, Prefect, Dagster, or similar technologies.
Experience working with cloud platforms and modern data technologies such as AWS, Azure, Snowflake, NoSQL databases, and CI/CD pipelines.
Strong understanding of data modeling, performance optimization, data governance, and secure data handling practices.
Excellent analytical, troubleshooting, communication, and collaboration skills.
Experience supporting analytics, research, or data-intensive business environments is strongly preferred.

Responsibilities

Design, develop, and maintain scalable data pipelines, ETL/ELT workflows, and integration processes across multiple data sources.
Build and optimize enterprise data models, databases, data warehouses, and cloud-based storage solutions to support reporting and analytics.
Ensure data quality, integrity, availability, and security through validation, monitoring, troubleshooting, and performance tuning.
Collaborate with analysts, economists, researchers, developers, and business stakeholders to gather requirements and deliver effective data solutions.
Implement workflow orchestration and automation tools to streamline data movement and processing.
Support migration of data pipelines and workloads between on-premises and cloud environments.
Develop and maintain scripts, services, and reusable components using Python, SQL, and other relevant programming languages.
Perform root cause analysis of data and process issues and recommend improvements to architecture, performance, and governance.
Create and maintain technical documentation, standards, and best practices for data engineering and platform operations.
Provide technical leadership and mentorship to junior team members while promoting DataOps, CI/CD, and engineering best practices.