Senior Data Architect

Job Title: Senior Big Data Architect/ Developer
Location: Washington, DC (Onsite) 

Job Description: 
Work Experience:
• 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.

Technical Skills:
• Bachelor’s degree in computer science, Information Technology, Engineering or a related technical field and at least 7 years of related experience; advanced degree preferred.
• Advanced working knowledge of SQL and experience working 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 working with large-scale data systems, including distributed computing, scalable data processing, data storage architecture, and optimization of high-volume data 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.
• Experience performing root cause analysis on internal and external data and business processes to answer business questions and identify opportunities for improvement.
• 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.