Enterprise Data Analyst

the USO•Arlington, VA

4d•Onsite

About The Position

The Enterprise Data Analyst supports the enterprise data function by serving as a first point of contact for data requests across the organization, conducting investigative and exploratory analyses, and helping maintain the integrity and usability of enterprise data assets. This role operates at the intersection of operational complexity and analytical inquiry, and requires someone who can hold ambiguity, navigate multiple competing priorities simultaneously, and use analytical tools to surface emergent issues and opportunities. The Enterprise Data Analyst works across organizational functions and stakeholder types, translating requests and needs, scoping incoming requests, and identifying where data breaks down, diverges, or misleads across systems. While reporting and dashboard responsibilities are part of this role, it is primarily an investigative and operational role.

Requirements

Bachelor’s Degree in a relevant field or equivalent demonstrated experience. Fields that reflect operational, research or analytical operations are of particular interest (public administration, research operations, public health or social science, policy analysis, or similar).
3-5 years of progressively responsible experience in a role that required analytical and systems thinking applied to real operational problems, where work was defined by complexity not by clean specifications.
Demonstrated proficiency in python for data analysis and exploration.
Proven ability to work across functional teams with competing priorities and varying levels of data literacy, including experience communicating technical findings to non-technical audiences.
Strong interpersonal, and written and verbal communication skills; this role requires as much skill in translating and framing as in producing analyses.
Excellent problem-solving and critical-thinking abilities.
Must show initiative, self-motivation, creativity, and desire to innovate with strong attention to detail and quality.
Ability to work independently and manage multiple projects simultaneously.
Ability to learn and stay current with industry trends and best practices in enterprise data, data analytics and business intelligence.
Ability to obtain and maintain proper credentials necessary to access USO Center locations and facilities including but not limited to security, credit and/or background screening, SOFA status, valid driver’s license.
Must be a strong advocate of the USO’s mission to strengthen the well-being of the people serving in America’s military and their families.

Nice To Haves

Relevant experience in nonprofit, government, military-adjacent, or mission-driven organizational context is a plus.
Additional experience with SQL is preferred.
Experience working with or alongside enterprise CRM platforms with understanding of how data integrity issues arise through system use over time; experience with Salesforce Non-Profit Cloud strongly preferred.

Responsibilities

Conduct investigative and exploratory analysis across data sources and systems (using python, SQL) to surface patterns, anomalies, and data quality issues with the potential to impact business decisions and strategy.
Serve as primary cross-functional intake point for enterprise data requests, clarifying ambiguous asks, identifying underlying questions, and scoping work appropriately as a coordinating function.
Work across multiple enterprise systems to understand how data flows between platforms, where definitions diverge, and where records degrade or conflict over time.
Translate between technical and non-technical stakeholders across functions; able to speak creditably to mission delivery program managers, fundraising staff, finance, and technical administrators.
Support the documentation of data intake processes, operational workflows, and analytical findings in ways that make the enterprise data function more accessible and scalable for the organization.
Identify data quality issues, definitional inconsistencies, ontological drift, and systemic risks as a routine part of analytics work, escalating and flagging findings to inform data governance and remediation priorities.
Contribute to the development of lightweight operational tools, scripts, and automated queries that reduce manual data handling across the organization.
Other duties as assigned.