Senior IT Data Engineer

Senior IT Data Engineer contract role supporting the Federal Reserve Board’s Division of Research & Statistics (R&S) DATA section in Washington, DC (onsite).

Responsibilities

• Expand and optimize data and data pipeline architecture.
• Optimize data flow and data collection for economic policy and research teams.
• Design and develop data delivery architecture for optimal performance and delivery.
• Improve existing data systems and/or build new systems from the ground up.
• Optimize or redesign the R&S division’s data architecture to support next-generation data initiatives.
• Support economists and technical experts.
• Provide service-minded support across multiple teams and systems with a self-directed approach.
• Design and communicate enterprise information architecture across conceptual, logical, and physical levels.

Requirements

• Bachelor’s degree in computer science, Information Technology, Engineering, or a related technical field, plus at least 7 years of related experience; advanced degree preferred.
• Advanced working knowledge of SQL.
• Experience with relational database platforms including PostgreSQL, Microsoft SQL Server, and MySQL.
• Advanced working knowledge of Python, R, and other scripting languages used for data engineering and analytics.
• Experience with large-scale data systems: distributed computing, scalable data processing, data storage architecture, and optimization for high-volume workloads.
• Experience designing, developing, and automating ETL/ELT workflows and data integration pipelines.
• Experience building, optimizing, and maintaining scalable databases, data pipelines, and data processing frameworks.
• Experience with workflow orchestration and pipeline automation tools such as Apache Airflow, Prefect, Dagster, or AWS Step Functions.
• Experience migrating workflows and data pipelines between on-premises and cloud environments.
• Experience processing, analyzing, and integrating structured and unstructured data sources.
• Experience developing in Linux environments and using source control platforms such as GitLab and/or GitHub.
• Ability to perform root cause analysis on internal and external data and business processes to answer business questions and identify improvement opportunities.
• Ability to design and communicate enterprise information architecture at conceptual, logical, and physical levels.
• In-depth experience designing and implementing database, data lake, and enterprise data platform solutions.
• Strong hands-on software engineering and implementation experience, including development, testing, and deployment of data applications and services.
• Excellent oral and written communication skills with a strong customer service orientation.
• Exceptional analytical, problem-solving, and troubleshooting skills.
• 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 and scripting languages such as Java, Scala, JavaScript, or Perl.

Technologies

• SQL
• PostgreSQL
• Microsoft SQL Server
• MySQL
• Python
• R
• Apache Airflow
• Prefect
• Dagster
• AWS Step Functions
• Linux
• GitLab
• GitHub
• NoSQL
• Graph database technologies
• Machine learning models
• AWS
• Microsoft Azure
• Snowflake
• Change Data Capture (CDC)
• CI/CD pipelines
• DataOps
• Java
• Scala
• JavaScript
• Perl

Benefits

• Eligible employees health and welfare benefits coverage options including medical, dental, vision, spending accounts, life insurance, voluntary plans.
• Participation in a 401(k) plan.