4+ years of experience in Business Analysis, Data Analytics, or a similar role, preferably within a Support or Customer Experience function
Advanced proficiency with Tableau & Excel for data visualization and dashboard development
Strong experience working with Salesforce (SFDC) data, objects, and reporting structures
Proven ability to work with large, complex datasets using SQL or equivalent querying tools
Excellent communication and stakeholder management skills; able to distill complex data into clear narratives
Strong problem-solving skills and business acumen, with a bias toward action and impact
Familiarity with Customer Support metrics (CSAT/DSAT, NPS, FCR, response times, etc.)
Solid proficiency in MS Office suite (especially Excel), and Google Workplace
High degree of judgment and discretion in managing stakeholder concerns, with strong problem solving skills and able to prioritize tasks and concerns
Ability to analyze, manage and handle stakeholder expectations
Ability to effectively prioritize multiple tasks, projects and deadlines simultaneously
Excellent verbal communication skills
Responsibilities
Develop, maintain, and optimize dashboards and reports in Tableau to visualize support KPIs, operational trends, and business outcomes
Partner closely with stakeholders to understand business goals and translate them into scalable, data-driven solutions
Analyze large datasets from Salesforce (SFDC) and other internal systems to extract meaningful insights and recommendations
Support ongoing improvements to our data infrastructure and reporting processes; contribute to the design and documentation of data pipelines and data models
Monitor and improve data quality across systems and help build trust in our support reporting ecosystem
Identify automation opportunities and support operational excellence initiatives within the Support organization
Collaborate with Data Engineering and other Analytics teams to align on definitions, metrics, and best practices
Stay current on developments in AI, advanced analytics, and data tooling to identify opportunities for innovation in support analytics