AI Analyst, BI

• Own the technical design, enhancement and ongoing evolution of AI-enabled BI automation capabilities.

• Own the technical design, enhancement and ongoing evolution of AI-enabled BI automation capabilities.
• Develop scalable solutions for report onboarding, scheduling, refresh, monitoring, quality validation and delivery.
• Convert manual BI processes into reusable and configurable automation workflows.
• Define and maintain the technical roadmap with BI, Technology and business stakeholders.
• Evaluate AI and automation opportunities based on business value, feasibility, scalability and adoption potential.
• Ensure solutions can support multiple regions, clients, report types and BI hubs.

• Design and develop scalable, cloud-native applications using Python.

• Design and develop scalable, cloud-native applications using Python.
• Build and maintain APIs, backend services and business-rule engines.
• Develop reliable solutions using object-oriented programming, reusable components and established design patterns.
• Perform automated data validation, missing-value detection, duplicate analysis, anomaly detection and variance analysis using Pandas, Polars or equivalent frameworks.
• Develop integrations across BI reporting, automation, quality-control and delivery platforms.
• Integrate Power Platform applications with Azure services, SQL Server, REST APIs, SharePoint, Microsoft Teams, Power BI and other enterprise systems.
• Optimize applications for performance, reliability, maintainability and scalability.

• Develop and integrate enterprise Generative AI solutions using services such as Azure OpenAI, Llama, LangChain and vector search.

• Develop and integrate enterprise Generative AI solutions using services such as Azure OpenAI, Llama, LangChain and vector search.
• Build AI-enabled solutions using Azure AI Foundry, Azure AI Search, Microsoft Copilot Studio, AI Builder, custom prompts, agent flows and generative actions.
• Apply Retrieval-Augmented Generation, prompt engineering and structured AI workflows to BI use cases.
• Use AI to generate executive summaries, business insights, recommendations and exception explanations.
• Design controls to validate AI-generated output before it is used in business processes.
• Evaluate Small Language Models for cost-efficient or low-latency deployments.
• Explore AI agents and intelligent workflows for report creation, quality validation, monitoring and operational support.
• Apply deterministic validation wherever accuracy, traceability and repeatability are required.

• Understand the complete BI report lifecycle, including requirement intake, report creation, refresh, validation, approval and delivery.

• Understand the complete BI report lifecycle, including requirement intake, report creation, refresh, validation, approval and delivery.
• Automate repeatable activities across Excel-based reporting and other BI platforms.
• Develop configurable quality rules for data checks, business validation and change detection.
• Support report-level and worksheet-level checks such as blanks, duplicates, formula continuity, reporting periods, product or market changes and variance thresholds.
• Design monitoring and exception-management capabilities that enable users to identify and resolve failures quickly.
• Partner with BI subject-matter experts to convert business validation requirements into scalable technical rules.
• Establish measurable quality controls and audit trails for automated processes.

• Design, develop and support enterprise applications using Power Apps, Power Automate and Dataverse.

• Design, develop and support enterprise applications using Power Apps, Power Automate and Dataverse.
• Build user interfaces, workflow automation, approval processes and data-driven applications aligned with BI operational requirements.
• Design secure Dataverse data models, roles, permissions and integration patterns.
• Apply Power Platform governance, Data Loss Prevention policies, environment strategy and reusable solution standards.
• Use custom connectors and APIs to extend Power Platform capabilities and integrate with enterprise services.

• Contribute to scalable, extensible and secure solution architecture.

• Contribute to scalable, extensible and secure solution architecture.
• Develop distributed, event-driven and microservices-based solutions where appropriate.
• Work with Azure, AWS or GCP cloud services based on approved enterprise architecture.
• Develop and integrate Azure capabilities including Azure Functions, Azure SQL, Azure Storage, Microsoft Entra ID and Azure Data Factory.
• Implement CI/CD pipelines, automated testing and version-control practices using Git.
• Manage Power Platform Application Lifecycle Management using solutions, connection references, environment variables, service principals and controlled DEV-to-TEST-to-PROD deployments.
• Support containerization and orchestration using Docker and Kubernetes where required.
• Apply Infrastructure as Code practices using Terraform, Pulumi or equivalent tools.
• Implement logging, monitoring and observability using Prometheus, Grafana, OpenTelemetry or equivalent tools.
• Ensure compliance with enterprise security, privacy, access-control and engineering standards.

• Monitor application performance, automation success rates and production reliability.
• Lead technical investigation and root-cause analysis for production incidents.
• Implement preven

• Strong proficiency in Python and object-oriented programming.

• Strong proficiency in Python and object-oriented programming.
• Strong understanding of data structures, algorithms and software design patterns.
• Hands-on experience developing APIs and backend services.
• Experience with Pandas, Polars or similar data-processing frameworks.
• Experience with Pytest or comparable automated testing frameworks.
• Experience with Git, CI/CD pipelines and DevOps practices.
• Experience with Azure, AWS or GCP.
• Practical experience with Azure Functions, Azure SQL, Azure Storage, Microsoft Entra ID and Azure Data Factory.
• Understanding of distributed systems, microservices and event-driven architecture.
• Strong debugging, performance-optimization and root-cause-analysis skills.

• Hands-on experience developing Generative AI or language-model-based applications.

• Hands-on experience developing Generative AI or language-model-based applications.
• Experience with Azure OpenAI, LangChain, Llama or equivalent technologies.
• Hands-on experience with Azure AI Foundry, Azure AI Search, Microsoft Copilot Studio, AI Builder, custom prompts, agent flows or generative actions.
• Knowledge of Retrieval-Augmented Generation, vector databases and vector search.
• Experience with prompt engineering and structured AI-output validation.
• Ability to combine AI capabilities with deterministic business rules.
• Understanding of responsible AI, data privacy, security and model limitations.

• Experience with Business Intelligence or reporting automation.

• Experience with Business Intelligence or reporting automation.
• Strong hands-on experience with Microsoft Power Platform, especially Power Apps, Power Automate and Dataverse.
• Understanding of report refresh, data validation, quality-control and delivery processes.
• Strong knowledge of SQL and relational databases.
• Strong practical knowledge of SQL Server, including complex queries, views, stored procedures, permissions, performance optimization and application integration.
• Experience handling structured data, Excel workbooks or comparable reporting outputs.
• Ability to translate BI and business requirements into scalable technical solutions.
• Experience developing configurable data-quality or business-validation rules.
• Experience with Power Platform Application Lifecycle Management, including solutions, connection references, environment variables, service principals and DEV-to-PROD deployment controls.
• Experience integrating Power Platform applications with Azure, SQL Server, APIs, SharePoint, Microsoft Teams, Power BI and other enterprise systems.

• Experience owning technical features or solutions end to end.

• Experience owning technical features or solutions end to end.
• Ability to independently manage the complete product lifecycle, covering requirements, architecture, development, testing, deployment, monitoring and production support.
• Ability to communicate complex technical concepts in simple business language.
• Experience working with business stakeholders, architects and engineering teams.
• Ability to conduct solution demonstrations, requirement discussions and technical reviews.
• Ability to mentor developers and establish engineering standards.

• Experience with Power BI, Excel automation, Power Query or other enterprise reporting platforms.

• Experience with Power BI, Excel automation, Power Query or other enterprise reporting platforms.
• Experience developing automated report creation, report refresh or report-quality solutions.
• Experience with Small Language Model deployment or fine-tuning.
• Knowledge of SQL and NoSQL persistence models.
• Familiarity with Terraform, Pulumi or other Infrastructure as Code tools.
• Experience with Prometheus, Grafana, OpenTelemetry or comparable observability tools.
• Experience with Docker and Kubernetes.
• Familiarity with GitHub Copilot or equivalent AI-assisted development tools.
• Experience working in Agile or Scrum delivery models.
• Experience supporting enterprise applications in a production environment.
• Exposure to workflow automation, robotic process automation or agent-based solutions.

• Business requirements and technical architecture.
• Hands-on development and technical leadership.
• AI innovation and production reliability.
• Global stakeholder engagement and detailed problem-solving.
• Short-term delivery needs and long-term platform scalability.

• Flexible working environment

• Flexible working environment
• Volunteer time off
• LinkedIn Learning
• Employee-Assistance-Program (EAP)