CXi Analyst

Description

CX Data Analyst - Reporting Visualisation

Location: El Salvador

Department: Customer Experience

Reports To: Director, CX Shared Services

Role Overview

The CX Data Analyst will develop and maintain high-quality dashboards and reports that surface intent-level and service-level insights across the Money Transfer segment.

This role leverages data from various sources including ticketing, telephony, AI platforms and core systems to analyse trends, contact drivers, and customer/agent experiences, with an explicit focus on offline processes and the metrics that comprise contact rate.

Key Responsibilities

• Power BI Development & Data Modelling
  • Create, maintain, and optimise descriptive and diagnostic Power BI dashboards and visualisations, applying robust semantic models, DAX measures, and governed datasets.
  • Engineer star schemas and subject-area marts (tickets, calls, transactions) that enable intent/service-level analysis and scalable refresh performance.
• Core CX Metrics & Insights
  • Define and maintain metric frameworks for Contact Rate, FCR, AHT, CSAT, Containment, abandonment, reopen, and resolution SLAs, segmented by intent, channel, tier, region, and product.
  • Build intent-detection and tagging logic (e.g., Zendesk tags, contact reasons) to attribute journeys end‑to‑end and identify pain points, drop‑offs, and automation opportunities.
• Data Engineering Collaboration & Governance
  • Work closely with data engineers/DBAs to provision high‑volume Zendesk and supporting channel datasets in a warehouse, move complex logic out of Power BI, and establish sandbox testing for safe iteration.
  • Implement refresh schedules, data quality rules, change controls, and documentation that align with BI platform capacity and reliability expectations.
• Executive Reporting (Weekly & Quarterly)
  • Support the development and refinement of concise weekly executive scorecards and quarterly deep‑dive capabilities that highlight contact rate, employee performance, deltas vs. targets, risks/opportunities, and recommended actions; deliver via Power BI apps and exportable briefings.
  • Partner with leadership to prioritise initiatives based on insight (e.g., self‑service adoption, process improvements), and track outcomes over time.
• Advanced Analysis & Decision Support
  • Use statistical tools and exploratory data analysis to detect trends/patterns and produce actionable recommendations that improve customer and agent experiences.
  • Partner with supporting systems such as Zendesk, telephony, messaging, and AI administrators to ensure CX insights drive omnichannel service design and operational decisions.

Qualifications & Skills

Education: Bachelor’s degree in data/computer science, statistics, or related field.

Experience: Hands-on Power BI development (models, DAX, performance tuning) with large, multi-source CX datasets eg. Zendesk, channel data such as voice, chats, social media, Appstore’s, transactional etc.

Technical Skills:

• Strong SQL; data modelling (star schemas); ELT collaboration; gateway/refresh management; dataset governance.
• Statistical analysis and visualisation best practices; ability to convert business requirements into metric definitions and insight stories.

Soft Skills: Clear communication, structured storytelling for executives, analytical rigor, problem‑solving, and stakeholder management.

Measures of Success

• Operational BI Excellence
  • Report accuracy, reliability and timeliness; reduction in refresh failures/capacity incidents; adherence to governance.
  • Query/model performance (e.g., dataset size optimization, visual load times) and SLA compliance for weekly/quarterly deliverables.
• Insight Quality & Adoption
  • Coverage and accuracy of intent/service‑level tagging; uplift in executive and operational usage (views / number of users).
  • Number of insights leading to measurable improvements in CSAT, FCR, AHT, containment, and abandonment.
• Business Impact
  • Documented outcomes from recommended actions (e.g., self‑service adoption, process changes), with before/after metric movement.
  • Stakeholder satisfaction with weekly scorecards and quarterly deep‑dives (survey/feedback).

Tools & Data Sources

• Primary: Power BI, SQL, Zendesk datasets, channel datasets (eg. Voice, chats, social etc), trading platform data (warehouse‑provisioned where feasible).
• Supporting: BI apps/workspaces for executive distribution; governed semantic models and DAX libraries.