Principal Data Architect/Engineer - R&S

Job Description - Principal Data Architect/Engineer - R&S (R025792) Always verify and apply to jobs on the official Federal Reserve Board career site or through verified Federal Reserve Board social media channels. Principal Data Architect/Engineer - R&S - R025792 Primary Location : DC-Washington Employee Status : Regular Overtime Status : Exempt Job Type : Standard Work Shift : 1st Shift Relocation Provided : Yes Compensation Grade Low : FR PAY GRADE 28 Compensation Grade High : FR PAY GRADE 28 Minimum Salary : $144,500.00 Maximum Salary : $210,500 Posting Date : Aug 7, 2026 Position Description Minimum Education Bachelor's degree or equivalent experience Minimum Experience 8 Summary Directs the process for and/or participates in defining, visualizing, designing and/or developing data architecture, platforms, metadata, models (e.g., metamodels, conceptual, logical, physical), strategy, and/or roadmaps. Models relationships between concepts represented by data (e.g., metamodels for metadata). Owns and/or participates in strategic thought leadership, market analysis, technical assurance, and data governance related to the development, evolution and delivery of the information architecture domain as aligned to the business. Provides context and perspective in evaluation and design beyond the immediate and stated scope of work. Collaborates with delivery teams to participate in solution design (as part of data extraction, load, and transformation, as well as for data analysis, storage, and processing solutions) or artificial intelligence solutions and directs the process to and/or independently designs data-related portions of the DevOps pipeline. Shows subject matter expertise in data architecture and related disciplines. Works with teams as a subject matter expert in this area to enable and improve solution design and delivery around data. Duties and Responsibilities Independently creates and documents standards, design patterns, and best practices for data-related software development, incorporating appropriate constraints (e.g., data management best practices, information security such as access enforcement based on data sensitivity, systems controls, systems monitoring, regulatory constraints such as data retention, etc.). Directs the process for and/or participates in visualizing and designing the enterprise data management framework based on industry best practices (such as Data Management Body of Knowledge, DMBoK). Has expert knowledge of system development lifecycle, system maintenance, and system security. Directs and/or contributes to designing data-related portions of the DevOps pipeline (e.g., data model and database changes, data pipeline and automation) as an enabler for solution delivery team process. Decides the process for and participates in documenting information and data flow within the context of business processes or defined business outcomes, capturing required behaviors of the data based on end user feedback (including which parts of the organization generate and consume data, allowable values and conditionality, entity states, etc.). Directs the process for and/or participates in visualizing and designing the enterprise data management framework based on industry best practices (such as Data Management Body of Knowledge, DMBoK). Develops strategies to improve performance of data through advice on technology selection; data structure or layout; architectural choices; or other best practices. Has expert knowledge of system development lifecycle, system maintenance, and system security. Directs and may make the final decisions for and/or participate in defining data architecture frameworks and standards in alignment with enterprise data management principles and guidance, including data modeling (e.g., metamodels, conceptual, logical, physical), metadata management, data security, reference data such as product codes and client categories, and master data such as clients, vendors, materials, and employees. Has expertise in using version control and Agile best practices for the delivery of data in a DevOps pipeline using tools such as git, CI/CD, etc. Directs vertical alignment and integration analysis among different types of architectures including business architectures, data architectures, application architectures and technology architectures. Directs the process for and/or participates in conducting data extraction, ingestion, and loading to transform data to be accessible by users. Has expert knowledge of data warehouse and lake architecture, data file types, data delivery methods, ETL tools, data pipeline and automation, data management systems, data storage systems, artificial intelligence and machine learning modeling and design, and associated best practices. Decides the process for and/or participates in designing, developing, and implementing solutions to improve technology efficiencies for data architecture. Stays up to date with the latest technology and business trends and innovations. Independently evaluates and/or defines technology and business requirements to identify areas for data architecture improvement. Directs the process for and/or participates in tool evaluation (e.g., proofs of concept, prototyping, etc.) and the selection process. Directs and identifies needs, structures the POC, and runs it for data related purposes. Directs the process for and/or participates in the process of building automated architectural workflows that gather, organize, manipulate, and transform data across platforms and systems to provide datasets that are accessible and fit for analysis. Governs large volumes of both structured and unstructured data by overseeing, designing, developing, and troubleshooting data flows to process large quantities of data (e.g., high-frequency data). Directs the process for and/or participates in architectural and technology review boards, standards setting bodies, and other strategic workgroups representing data architecture. Directs and/or participates in the development of organizational data governance policies and standards, data classification and ownership, data quality assurance, data privacy and security, data stewardship, data access and usage policies, date privacy and security, metadata standards, enterprise data definitions, enterprise taxonomy standards. Directs the design of data architectures to safeguard digital data throughout its entire lifecycle to protect it from corruption, theft, or unauthorized access. Directs the architecture design of protection and handling of data at rest and in transit based on federal security agency defined maturity model. Directs the process for and/or participates in harnessing distributed computing for big data engineering, visualization, and exploration. Has expert skilled at leveraging big data analytics applications. Has expert knowledge to use programming languages for data process, transformation, analysis, and scripting tasks. Uses expert knowledge of distributed computing principles to design solutions for large-scale data processing. Directs, mentors and/or participates in the process to define reference data architectures and reusable design patterns for data related services or components. Directs and/or performs quality data architecture reviews on all work materials and information; and follows up with others to ensure that agreements and commitments have been fulfilled. Requires expert knowledge of key components of cloud computing (i.e., Software-as-a-Service, Infrastructure-as-a-Service, and Platform-as-a-Service) and one or more cloud technology platforms (i.e., Amazon Web Services, Microsoft Azure). Thinks strategically and holistically about current and future requirements to plan for and implement new technology adoption, transformation, consolidation, and/or incremental improvements. Has expert knowledge of technology options available in the market and skilled at assessing their viability for meeting division and/or Board needs. Uses expert knowledge of risk management principles to identify, evaluate, and mitigate risk. Mentors and/or collaborates with business partners in data governance and data management efforts to direct the process for and/or participate in data architecture designs and provide input on functional requirements, designs, schedules, or potential problems. Analyzes and/or directs the process of examining business needs and software requirements to determine feasibility of design within time and cost constraints. Collaborates with delivery teams to guide solution design (as part of data extraction, load, and transformation, as well as for data analysis, storage, and processing solutions) and to ensure design patterns are being used appropriately and that the solution designs conform with direction of the data architecture road map. Independently analyzes and translates customer support inquiries into technical requirements and develops plans/strategies for resolution of issues and/or development of solutions using broad knowledge of the Board’s and division’s technology environment. Guides the resolution of and/or troubleshoots data architecture issues from their start through their resolution. Mentors more junior staff and/or participates in providing data support services to end users, which includes troubleshooting data-related problems and answering questions about the Board's data assets. Independently meets regularly with stakeholders to discuss needs, research and collect information about business operations, and define requirements and use cases. Uses complex analysis methodologies to identify business processes. Decides appropriate solutions and monitors satisfaction. Represents unit, branch, or division in stakeholder meetings, coordinates with stakeholders to resolve data questions, and participates on task forces and committees, both internal and external to the Board. Independently negotiates agreements and commitments by facilitating communication with stakeholders from initial requirements to final implementation. Independently partners, communicates, and/or liaises with customers, staff, project team members, project sponsors and/or stakeholders to manage expectations, communicate or gather project information, and/or ensure customer satisfaction. Position Requirements The Data Architecture, Technology, and Analytics (DATA) section within the Research and Statistics Division is tasked with transforming how the Federal Reserve Board's Division of Research and Statistics (R&S) ingests, organizes, uses, and visualizes data. The DATA section seeks an experienced, detail-oriented, and hands-on Data Architect to join our growing team. In this role, the Data Architect will lead or work closely with other data architects, data engineers, and related professionals whose mission is to modernize and maintain the division's data architecture and to develop data pipelines, tools, and processes that are optimized for economic policy and research. The ideal candidate is an experienced hands-on data modeler and data engineer with working knowledge of database administration. The Data Architect must have a service mindset, be self-directed, and 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. Duties and Responsibilities · Document the division's current data architecture and maintain an accurate view of the division's data ecosystem. · Participate in developing future state data architecture standards, guidelines, and principles. · Create short-term tactical solutions, advance toward long-term objectives, and develop an overall data lifecycle management roadmap. · Migrate workflows and data pipelines between on-premises and cloud environments. · Analyze business processes, applications, and source data to understand dependencies, anomalies, and implicit business rules that impact the ability to manage division data. Review and analyze data models and processes to optimize and modernize the division's data architecture. · Create data solution designs for economic policy and research projects (conceptual model, integration model, sourcing) in alignment with the division's research needs and data strategy. · Define specifications and implement database structure (logical and physical data models), backup, recovery, and access security. Develop and maintain a formal description of data and data structures including data models, data flow diagrams, data dictionaries, and technical metadata. · Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. · Collaborate with research and business teams to improve data models that feed analytics and visualization tools, thereby increasing data accessibility while fostering data-driven decision making across the organization. · Establish methods and procedures for tracking data quality, completeness, redundancy, and improvement. · Design, develop, and automate ETL/ELT workflows and data integration pipelines. · Build and optimize large-scale data systems, including distributed computing, scalable data processing, and data storage architecture. · Develop, test, and deploy data applications and services using software engineering best practices. · Maintain knowledge of evolving trends in technology to assist in developing innovative approaches that deliver value; develop understanding of business requirements and processes in order to assist in identifying technologies that meet the requirements. · Implement and maintain CI/CD pipelines and DataOps platforms. · Provide technical leadership and guidance on database design, data warehousing, and enterprise data platform solutions. Required Qualifications · Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical field. · Minimum of 8+ years of related experience in data engineering and architecture. · Advanced working knowledge of SQL and experience with relational database platforms (PostgreSQL, Microsoft SQL Server, MySQL). · Hands-on experience creating and managing enterprise-level data architecture for an organization. · Hands-on experience developing end-to-end data architectures, from the point of initial data ingestion to the management and transmission of finished products and services. · Hands-on experience developing and managing data architecture governance policies and procedures, and leading data architecture governance activities. · Hands-on experience designing complex data structures (at the conceptual, logical, and physical levels) to support different use cases (e.g., transaction processing, analytics) using different data representations (e.g., entity-relationship and data flow diagrams, JSON and XML schemas). · Advanced working knowledge of Python, R, and other scripting languages used for data engineering and analytics. · Demonstrated experience working with large-scale data systems and optimization of high-volume data workloads. · Proven experience designing, developing, and automating ETL/ELT workflows and data integration pipelines. · Experience building, optimizing, and maintaining scalable databases and data processing frameworks. · Experience with workflow orchestration and pipeline automation tools (Apache Airflow, Prefect, Dagster, or AWS Step Functions). · Experience implementing and maintaining CI/CD pipelines and DataOps platforms. · Proficiency developing in Linux environments and using source control platforms (GitLab, GitHub). · In-depth experience designing and implementing database, data lake, and enterprise data platform solutions. · Strong hands-on software engineering experience, including development, testing, and deployment. · Ability to design and communicate enterprise information architecture at multiple abstraction levels. · Excellent oral and written communication skills with a strong customer service orientation. · Exceptional analytical, problem-solving, and troubleshooting skills. · Ability to work independently and self-direct while supporting multiple teams and systems. Preferred Qualifications · Advanced degree in Computer Science, Information Technology, Engineering, or related field. · 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 (AWS). · Experience implementing data warehouses utilizing Change Data Capture (CDC) methodologies. · Excellent understanding of key data security concepts (e.g., data masking, data encryption in transit and at rest) and the corresponding technologies to implement them. · Working knowledge of additional programming and scripting languages (Java, Scala, JavaScript, Perl). · Experience migrating complex data systems between on-premises and cloud environments. 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