Fiber Capacity Management Analyst

Fiber Capacity Management Analyst 100% Remote Long term Contract Rate: $40/hr. On W2 Note: No Sponsorship provided/No C2C/1099 USC's and Perm Resident (GC) are encouraged to apply Position Overview We are seeking a Fiber Capacity Management Analyst to support our network planning and engineering organization. This role is responsible for analyzing fiber capacity data across multiple systems, identifying network trends and priorities, and supporting long-term capacity planning decisions. The ideal candidate has a strong analytical mindset, basic data analysis experience, and familiarity with fiber networks and GIS. Key Responsibilities • Review and analyze Power BI dashboards, Excel reports, and internal capacity management tools • Identify key priorities and what data should be reviewed for capacity planning • Access multiple systems to evaluate current fiber capacity and network availability • Perform trending analysis and limited data modeling to support planning decisions • Use GIS systems to verify where fiber is already deployed and identify gaps • Synthesize large data sets (thousands of records) to identify key issues and actionable insights • Manipulate, clean, and import Excel data into reporting tools or systems • Collaborate with planning leadership to provide recommendations based on data analysis • Support the planning organization until long-term staffing is in place Required Skills & Experience • Experience with Power BI (dashboard review, data interpretation, and basic development or edits) • Strong Excel skills including data manipulation, cleaning, and importing • Strong analytical and data synthesis skills • Familiarity with GIS systems and spatial data • Understanding of fiber networks and infrastructure • Ability to work independently and manage multiple priorities • Comfortable working in a remote environment Preferred Qualifications • Previous experience in telecom or ISP capacity planning • Background in network planning, engineering, or operations • Experience working with large data sets and identifying key issues