Qlikview Qlik Sense Visualization (AI-Enabled Analytics)

Qlik Visualization (AI-Enabled Analytics)

Department: Connected Data – Integration, Data Quality & Support

Position Overview

This position sits at the intersection of data integration, data quality, business

intelligence, and emerging AI-driven analytics, making it ideal for someone who thrives

in a fast-paced, data-driven environment.

Key Responsibilities

Qlik Visualization, Reporting & AI-Driven Insights

• Design, develop, and maintain interactive dashboards and reports using Qlik Sense

/ QlikView

• Translate business requirements into effective visualizations and KPIs

• Optimize Qlik applications for performance, scalability, and usability

• Establish and enforce visualization standards and best practices

• Evolve traditional dashboards into augmented analytics experiences (e.g.,

automated insights, anomaly detection, and narrative summaries)

• Enable self-service and conversational BI capabilities by supporting semantic

layers and natural language query interfaces

• Integrate AI/ML-driven insights (forecasting, trend detection, root cause analysis)

into reporting solutions

• Partner with stakeholders to shift from descriptive reporting to predictive and

prescriptive analytics

Data Integration, Modeling & Semantic Layer Development

• Collaborate with data engineering teams to support Connected Data integration

initiatives

• Build and maintain data models optimized for analytics, reporting, and AI

consumption

• Perform data transformation and validation to ensure consistency across sources

• Develop and enhance semantic data layers that standardize business logic and

enable scalable analytics across BI and AI tools

• Support the adoption of modern data architectures (lakehouse, cloud-based,

API-driven data access)

Data Quality, Governance & Trust in AI

• Monitor and improve data quality across multiple systems and pipelines

• Identify data anomalies, root causes, and recommend corrective actions

• Support data governance initiatives, including documentation and lineage tracking

• Ensure data readiness for AI use cases, including reliability, explainability, and

consistency of outputs

• Contribute to establishing standards for trusted data products and AI-enabled

reporting

Support, Innovation & Stakeholder Engagement

• Act as a key point of contact for business users regarding reporting and analytics

needs

• Provide support, troubleshooting, and enhancements for existing Qlik applications

• Work closely with cross-functional teams to prioritize and deliver analytics

solutions

• Educate business users on new analytics capabilities, including AI-driven

insights and self-service tools

• Continuously evaluate and pilot emerging technologies in BI, AI, and data

visualization to improve user experience and decision-making

Qualifications

Required

• Bachelor’s degree in Data Analytics, Computer Science, Information Systems, or

related field

• 5 years of experience in data analytics or business intelligence roles

• Strong expertise in Qlik Sense and/or QlikView development

• Experience with data modeling, ETL processes, and relational databases (SQL)

• Demonstrated knowledge of data quality principles and data governance

• Strong analytical, problem-solving, and communication skills

• Experience working in enterprise data integration environments

• Familiarity with cloud data platforms (AWS preferred)

• Experience with scripting languages or tools (Python, PowerShell, etc.)

• Exposure to AI/ML concepts or augmented analytics platforms

• Experience building or supporting semantic layers or metrics layers

• Familiarity with natural language query tools, copilots, or conversational BI

• Knowledge of transportation, logistics, or fleet data (a plus)

Key Competencies

• Data storytelling and visualization excellence

• Attention to detail and data accuracy

• Cross-functional collaboration

• Proactive problem-solving mindset

• Ability to manage multiple priorities in a dynamic environment

• Curiosity and innovation in applying AI to analytics and reporting

• Ability to translate emerging technologies into practical business value

• User-centric mindset focused on simplifying access to insights