Financial Data Analyst (Financial Feeder System Concentration)

Job description

At Significance, we believe the best results come from investing in great people. As a woman-owned consulting firm supporting federal civilian and Department of Defense customers, we bring together talented professionals who are passionate about solving complex challenges and making a meaningful impact. We're proud of the culture we've built - one rooted in trust, collaboration, respect, and genuine relationships. Our people are empowered to share ideas, grow their careers, and deliver exceptional results while supporting missions that matter. It's a culture we're proud of, and one that has earned us recognition as a Washington Business Journal Best Place to Work for seven consecutive years. Significance is seeking a **Financial** **Data Analyst** to join our growing team supporting **Navy Pacific in O‘ahu, Hawaii**. This is a hybrid position is based in Oʻahu and typically requires onsite work 2–3 days per week, with some weeks fully remote. Candidates must possess an **active Secret clearance**, although an **Interim Secret clearance will also be accepted**. The Financial Data analyst specialize in Navy FM data environments to support ongoing financial management modernization and analytics efforts across Navy ERP and associated Navy business systems. The analyst will work closely with comptroller organizations, functional experts, and technical teams to build meaningful, accurate, and actionable reports, dashboards, and data products. This role requires strong financial domain expertise combined with modern data analysis skill sets. The ideal candidate will be able to interpret FM business rules, understand how financial data moves across systems, and translate complex datasets into automated, transparent analytics that enhance decision-making and support audit readiness. ### Required Skills: - Minimum 4–6+ years of full-time (excluding internships) experience performing data analytics, business intelligence, or financial systems analysis within DoD organizations or Fortune 500 companies. - Strong prior experience supporting Financial Management (FM) operations, including working with General Fund or Working Capital Fund financial data, financial statements, reconciliations, or command-level reporting. - Demonstrated ability to translate FM business processes into analytic models, dashboards, and automated reporting solutions. - Hands-on experience using modern data analytics and visualization tools such as Power BI, Databricks, Qlik, Tableau, or equivalent platforms. - Prior experience working with structured and unstructured financial data sets, including data cleansing, transformation, normalization, and validation. - Ability to build repeatable data pipelines and automate reporting solutions that support month-end, year-end, or audit readiness activities. - Familiarity with Navy ERP financial data structures, interfaces, or integration points (FI, FM, GL, CO, AM, and Procurement/Expenditure data sets). - Understanding of FM processes such as budget execution, obligation tracking, cash management, reconciliation, trial balance validation, and financial statement compilation. - Working knowledge of Navy external systems (DCAS, DDRS, SLDCADA, DCPS, EDA, DTS, etc.) and experience analyzing data interactions between ERP and external feeds. - Ability to train end users on dashboards, analytics products, or data transparency tools—virtually or on‑site. - Experience documenting repeatable processes (desk guides, SOPs, workflows, source-to-target mappings). - Active U.S. DoD Secret clearance or eligibility to obtain one. ### Desired Skills: - Certifications such as CISA, CompTIA Data+, Microsoft Power BI Data Analyst Associate, or similar. - Experience conducting forensic analysis on FM datasets to identify anomalies, breaks, errors, or transaction-level discrepancies. - Experience with R, Python, SQL, or similar languages used for data engineering or analytics. - Background supporting DON or Navy ERP transformation, optimization, or enterprise-level analytics modernization efforts. - Creation of EDL pipelines with requisite QA testing and optimization monitoring.