Senior Data & Business Intelligence Analyst

Key Responsibilities

• Design, build, and maintain enterprise Power BI dashboards supporting federal Category Management, spend analytics, and governance reporting.
• Ingest and transform data from federal websites and APIs (e.g., SAM.gov, FPDS, USAspending, Advana).
• Develop and maintain Dataverse tables and SharePoint-based data repositories to support Power Apps workflows and enterprise data models.
• Collaborate with SharePoint team to automate pipelines using Power Query, Power Automate, or other tools to unify data from multiple systems.
• Create DAX measures, data models, and semantic layers to ensure accurate, scalable reporting.
• Partner with program managers, acquisition SMEs, and technical stakeholders to translate business requirements into dashboards and data workflows.
• Analyze large, complex datasets to identify trends, anomalies, and opportunities for cost avoidance and operational improvement.
• Document data models, refresh processes, and dashboard logic to support governance and sustainment.
• Support the development of a Category Management analytics platform including spend cubes, vendor normalization, SUM reporting, and sourcing insights.

Qualifications

• Education: Bachelor’s degree in Data Analytics, Statistics, or Business Analytics; Computer Science or Information Systems; Mathematics or a related quantitative field. Equivalent experience may substitute for degree.
• Experience: Approximately 1–3 years of related experience in Power BI dashboard development, data modeling, DAX, Power Query, experience pulling data from APIs or federal websites, and supporting federal clients (preferred).
• Technical Skills: Power BI (expert) — data modeling, DAX, Power Query; Power Platform (preferred) — Dataverse, Power Apps, Power Automate; SharePoint Lists / Dataverse for structured data storage; SQL (preferred) – for querying and joining relational data; API integration (REST, JSON, XML); Excel (pivot tables, advanced formulas); Strong understanding of data visualization best practices; Ability to explain complex data to non-technical audiences.
• Soft Skills: Strong communication and stakeholder engagement; Ability to work independently and manage multiple priorities; Attention to detail and commitment to data accuracy; Curiosity, problem-solving mindset, and willingness to learn new tools.