Senior Network Data Analyst

Job Description: Senior Network Data Analyst / Network Performance Analytics Specialist Location: Sydney, NSW (Hybrid/Onsite) | Employment Type: Full-Time | Department: Network Analytics / Telecommunications About the Role We are seeking an experienced Senior Network Data Analyst to join our telecommunications analytics team.

This role is ideal for a data professional who thrives at the intersection of network engineering and data science — turning raw telco data into actionable business insights through advanced SQL, Python, and BI-driven dashboards. Years of Experience Required Minimum 8–10 years of overall experience in data analytics, business analysis, or network performance analysis within the telecommunications sector.

3+ years specifically in a senior/lead data analyst capacity, including dashboard design ownership and stakeholder-facing reporting. Prior exposure to multi-generation network technologies (2G/3G/4G-LTE/VoLTE/5G-NR) strongly preferred. Skills & Knowledge Required Technical / Analytical Strong proficiency in SQL for querying and manipulating large, high-volume datasets and fetching meaningful insights Working knowledge of Python for data analysis and automation Advanced Power BI/ Tableau skills, including Power Query (M) and DAX Familiarity with cloud data platforms — Microsoft Azure , Data Lakes , and ideally Google Cloud (Big.

Query, GA, GTM) Proficiency in Excel for ad-hoc analysis and reporting Automation & Collaboration Tools Power Automate for workflow automation and reporting efficiency SharePoint for document and data collaboration Jira and Confluence for Agile project tracking and documentation Domain Knowledge Understanding of telecom network KPIs (accessibility, retainability, mobility, throughput) Familiarity with network management tools Knowledge of network optimisation principles across 3G, 4G/LTE, VoLTE, and 5G-NR technologies Methodologies & Soft Skills Agile/Scrum working experience Key Performance Indicators for the Role Improvement in network performance metrics through data-driven interventions Increased dashboard/report adoption and stakeholder engagement Reduction in manual reporting time through automation