Analyst - Enterprise Data Analytics & Automation

Role overview

Application development and automation

• Build and deploy Power Apps canvas and model-driven applications using Dataverse.
• Automate workflows such as approvals, routing, notifications, SLA triggers, reminders, and escalations.
• Design solutions with access controls, audit trails, version history, data retention, and single sign-on.
• Manage requirements, design, build, UAT, production release, hypercare, and enhancements.
• Integrate applications with Power BI and support security assessments and secure access across OpCos.

Analytics, reporting, and data engineering

• Create data models, dashboards, visual reports, and KPIs to support business decisions.
• Develop and deploy Power BI scripts, use DAX and SQL, and document algorithms, models, and relationships.
• Assess ETL processes and build, monitor, and troubleshoot pipelines across Azure data services.
• Support Microsoft Fabric migration and optimization, including workspace, capacity, performance, and cost standards.
• Contribute to data governance, consistent KPI definitions, data lineage, and a single source of truth.

AI and delivery

• Use generative AI to support development of visuals, code, dashboards, and applications.
• Validate AI outputs and keep results explainable, traceable, and compliant with data policies.
• Work with business owners to gather requirements, conduct UAT, and obtain go-live sign-off.
• Document solutions and pipelines; provide user support, training materials, and demonstrations.
• Report project progress weekly and raise blockers early.

Experience and qualifications

• Minimum 5 years of Power Platform development experience.
• Hands-on production experience building and supporting Power Apps and Power Automate solutions.
• Minimum 3 years of software development lifecycle experience using one or more programming languages.
• Experience in data preparation and data warehousing; knowledge of SQL Server.
• The profile lists a bachelor's or master's degree in computer science or information systems technology and separately lists a bachelor's degree in any field.
• Exposure to Microsoft Fabric, Azure data services, and AI or machine learning for analytics is described as an advantage or exposure.

Skills and working style

• Must-have technical areas include application development, process automation, data analytics, data engineering, AI/ML, data governance, programming, financial analysis, project/program management, and business acumen.
• Communicate with business and technical teams; translate business problems into digital products.
• Analytical problem-solving, collaboration, client management, adaptability, documentation, and continuous improvement are emphasized.
• Telecommunications experience is preferred for familiarity with business KPIs.
• The role is an individual-contributor delivery position with no people-management responsibility.

Business context