Data Engineer II - Monetary Affairs - R024920

Primary Location : DC-Washington

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Employee Status : Regular

Overtime Status : Exempt

Job Type : Standard

Work Shift: : 1st Shift

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Relocation Provided: : Yes

Compensation Grade Low: : FR PAY GRADE 24

Compensation Grade High: : FR PAY GRADE 26

Minimum Salary: : $95,700.00

Maximum Salary: : $145000

Posting Date : Dec 17, 2024

Summary

Assists with designing and implementing data management infrastructure. Contributes to building and maintaining data management systems that combine core data sources into data repositories to enable reporting/visualization and analysis of data. Assists with writing or improving code to handle complex data processing tasks. Assists with product development of internal systems, tools, and platform. With regular direction, identifies key opportunities for improvement and technical/process enhancement to increase operational efficiencies. Helps to explore and query datasets, cleans, and transforms data, and may develop dashboards and visualizations. Has an intermediate ability to use tools and technologies that protect the security of Board data.

Duties and Responsibilities

• With regular guidance, influences building and architecting next generation data management platforms on a group of core technologies. Contributes to developing, maintaining, and optimizing data management solutions that ensure high availability of data availability, data scalability, data quality, data integrity and data security. Contributes to exploring new datasets, promoting data discovery and understanding, revising existing data and building and maintaining data views and aggregate data series of low complexity. Helps to query datasets and cleans/transforms data of low complexity.
• Has an intermediate understanding of new/key technologies and platforms and how to incorporate third party APIs and open source/reusable components. Uses intermediate knowledge of new/key technologies to begin to influence the implementation of innovative solutions.
• Contributes to utilizing lean and agile software development practices such as test-driven development, refactoring, continuous integration, and deployment, version control, and simple design to create quality, reusable- code. Assists with writing or improving code to handle complex data processing tasks, or rewriting old processes written in older languages. Contributes to collecting ongoing data updates from external sources to establish and maintain software code used to convert raw data into usable formats.
• With regular guidance, creates and maintains programs and processes necessary to provide data for production and research. Contributes to implementing processes and programs that monitor data quality, logging and responding to production issues, and ensures production data is always accurate and available for key stakeholders/customers and business processes that depend on it.
• Assists with product development of internal systems, tools and platforms supporting operational capabilities. Contributes to transitioning existing products out of legacy technology platforms. May contribute to creating new products as ad hoc requests arise.
• Assists with integrating data from multiple sources to employ simple features of integration technologies. Contributes to developing recommendations and providing guidance related to data integration strategy in order to meet future reporting and analytic needs.
• With regular guidance, influences the designing, constructing, and implementing of a database system to meet strategic needs. Contributes to building data management systems that combine core data sources into data repositories to enable reporting and analysis of data. Builds up skills related to developing and maintaining data pipelines that ingest data from a wide variety of structured, semi-structured, and unstructured data formats.
• With regular direction, identifies key opportunities for improvement and technical/process enhancement to increase operational efficiencies, address future technological needs, and reduce costs associated with the use of internal tools.
• Assists with safeguarding digital data throughout its entire lifecycle to protect it from corruption, theft, or unauthorized access. Has an intermediate ability to use tools and technologies that protect data in transit and/or at rest through processes like data masking, encryption, and redaction of sensitive information. Contributes to setting access permissions.
• Utilizes foundational to intermediate knowledge of key components of cloud computing and one or more cloud technology platforms. Assists with evaluating use cases to determine which cloud tools and services best fit a client’s needs.
• Contributes to gathering and analyzing various quantitative and qualitative data to provide useful information and actionable recommendations to clients. Based on data analysis, helps to illustrate and report data findings using intermediate knowledge of visual charts, figures, tables, and dashboards to tailor findings to specific audiences.
• Develops knowledge and awareness of and adheres to applicable governing standards.
• Assists with governing large volumes of both structured and unstructured data. Contributes to designing, developing, automating, and troubleshooting data flows and pipelines to process large quantities of data.
• With regular assistance, proactively troubleshoots, diagnoses, documents and resolves escalated support problems as assigned. Refines abilities in explaining technical problems/solutions to non-technical individuals, in order to provide context for how the issue was resolved.
• Assists with writing documentation for new and existing productions processes and data items. Helps to ensure up-to-date documentation is available and written in a clear and succinct manner.

*U.S. CITIZENSHIP REQUIRED*
About the Team:
The Division of Monetary Affairs supports the Board and the Federal Open Market Committee (FOMC) in their deliberation and decisions about interest rate and balance sheet policies and lender-of-last-resort responsibilities. Division staff conduct research and analysis on monetary policy issues pertaining to strategy, communications, implementation, transmission, and liquidity provision. The Monetary Statistics and Analysis (MSA) section manages a portion of the division's monetary statistics and data-related technology and governance activities. 
Essential Duties:

• Participate in the collection, processing, and validation of bank credit aggregates for the purpose of analysis and publication, including the H.8 statistical release, "Assets and Liabilities of Commercial Banks in the United States."
• Understand basics of bank balance sheets and develop knowledge of loan and securities classifications as outlined in the Call Reports
• Share responsibility for understanding underlying data sources for the aggregates, managing section data resources, improving the section's tools for analyzing bank microdata, and contributing to FOMC briefing materials on developments in bank balance sheets, and weekly updates based on incoming data. 
• Perform statistical analyses including seasonal adjustment and stratified sampling, and data edit tolerances.
• Work with other team members to produce time-sensitive materials to be included in the official statistical release.
• Use statistical programming to build, manage, analyze, and creatively present data to senior division staff, policymakers, and the public at large.
• Use PostgreSQL, R, dashboards in R using Posit (Shiny), and other tools to build automated reports, dashboards, and interactive products that support exploratory data analysis and review.
• Candidates can expect to work with the following technology stack: R, dashboards in R using Posit (Shiny), PostgreSQL, Python, Git, LaTeX, Linux, and some legacy tools. 
• Play a lead role in modernizing on-premises data pipelines and software away from legacy tools and preparing them for migration to cloud platforms.
• Conduct software testing, support, and maintenance.
• Document solutions by developing documentation, flowcharts, layouts, diagrams, and charts. 
• Effectively communicate, both in writing and verbally, with personnel and stakeholders across all organizational levels. 
• Participate in project management activities such as planning, scheduling, developing and implementing user stories, breaking down work into tangible activites, and identify and manage risks. 

Required Qualifications:

• A bachelor's degree in computer science, data science, information technology, public policy, economics, or related field, and three (3) years of experience
• Demonstrated ability to build and manage data pipeline and dashboard solutions using R, and SQL
• Foundational knowledge in database design/development, data analysis, data security, technology compliance, and data flow management
• Demonstrated ability to support more senior staff with technical support, database administration, technical problem solving, technical documentation, data visualization, code creation/maintenance, data integration, and production development/maintenance
• Meticulous attention to detail in all tasks and deliverables

Desired Qualifications:

• Understanding of statistics, finance, or accounting combined with willingness to learn about banking and engage with users of banking statistics such as economists preparing reports for the FOMC. 
• Experience with creating dashboards in R or Python
• Experience with Agile project management techniques
• Familiarity with cloud-native services including data orchestration, architectures, or tooling for implementing efficient data pipelines in a cloud environment
• Exposure to modern data governance practices, like data stewardship, data cataloging and metadata management, data access controls (e.g., role-based access controls and attribute-based access controls, data masking, tokenization), compliance automation, data lineage tracking, and data quality management
• Troubleshooting both programming issues and data anomalies
• Proficiency in modern statistical software packages (e.g., R, SAS, STATA, MATLAB) for advanced data analysis, modeling, and visualization
• Experience integrating statistical software with big data platforms (e.g., Spark, Hadoop) to enable scalable data processing and predictive analytics