Senior Data Engineer

Location: Washington, DC (Hybrid, with on-site presence as required by the client)

Contract: IT Management and Governance Support Services (ITMGSS) Blanket Order Agreement (BOA), Task Order 1: Business Process Improvement (BPI) Support Services

Clearance/Screening Requirements: Candidates must be US Citizens and able to successfully undergo a background investigation.

Position Summary:

PBG's McLean, VA office is seeking a skilled and forward-thinking Data Engineer to join a critical Task Order focused on Business Process Improvement (BPI) for the Board of Governors of the Federal Reserve System (Board). As a vital member of a dedicated Agile sprint team, this individual will design, build, and maintain the data infrastructure essential for transforming the Board's economic and policy analysis capabilities. The Data Engineer will be responsible for creating robust data pipelines, transformations, and workflows, working side-by-side with Business Process Analysts to map current-state data flows and design modernized, target-state architectures. This role requires a strong technical foundation in data engineering, experience in data-intensive regulatory or financial environments, and the ability to help guide modernization efforts away from legacy systems.

Key Responsibilities:

The Data Engineer shall be responsible for the following (subject to evolving needs):

• Design, build, and maintain robust and scalable data pipelines, ETL/ELT processes, and complex data workflows to support economic analysis.
• Collaborate directly with business process analysts and architects to analyze current-state data flows and contribute to the design of target-state data architectures.
• Act as a technical subject matter expert for data engineering, actively supporting data modernization and migration initiatives away from legacy systems.
• Create and maintain technical documentation for data flows, dependencies, and processes to support business analysis and ensure architectural alignment.
• Implement solutions that adhere to best practices in data governance, data quality, metadata management, and access control.

Minimum Qualifications:

• A Bachelor's degree (BS/BA) in computer science, information systems, engineering, or a related technical field from an accredited institution.
• A minimum of 8 years of professional experience, with at least 3+ years leading in data engineering, data integration, or a related technical field.
• Demonstrated experience designing, developing data pipelines, data transformations, and data workflows.
• Experience working with relational and/or non-relational databases and data storage technologies.
• Ability to document data flows, data dependencies, and technical processes in support of business process analysis.
• Experience supporting data-intensive, analytical, research, financial, or regulatory environments.
• Experience using ETL/ELT framework and proficiency in programming language used for building pipelines (e.g., Python, R, SQL, Perl, Scala, etc.).
• Familiarity with data governance, data quality, metadata, and access control considerations.
• Experience working alongside business process analysts or enterprise architect to document current-state and target-state data architectures/processes.
• Ability to support modernization or migration efforts from legacy data environments.
• Experience working in agile, hybrid, or iterative delivery environments, including collaboration with cross-functional teams and incremental solution delivery.
• Strong analytical and problem-solving skills.

Highly Valued Qualifications:

• Experience supporting data pipelines used for modeling, forecasting, or analytical workloads.
• Demonstrated experience in analyzing interdependencies across data pipelines, repositories, analytical models, and workflows.
• Familiar with cloud-based data platforms and services (AWS preferred) and modern data engineering tools.
• Familiar with programming languages used for data analytics (e.g., R, SAS, Stata, etc.).
• Familiar with data pipeline and orchestration tools (e.g., Databricks, Apache Airflow, AWS Glue, Informatica, etc.).
• Experience working in environments with federated ownership models and complex governance structures.