About this role
Role Overview We are seeking an Analytics Engineer to design, build, and operate our analytics and automations as well as build of AI-powered automations and copilots using governed enterprise data. This role is responsible for delivering high-quality Power BI reporting, establishing and maintaining Microsoft Fabric and/or GCP BigQuery, and building business automations and applications using Python, Power Automate and Power Apps. You will be part of the Cloud & Service Management organization helping to evolve our self-service analytics, scalable data architecture, and automations—while ensuring security, performance, and governance across the platform. This is a hands-on role with ownership of both solution delivery and platform best practices. Key Responsibilities Analytics & Reporting
• Design, develop, and maintain reports and dashboards • Build and optimize semantic models using strong dimensional modeling (star schema) • Write and tune DAX measures with a focus on performance and usability • Implement Power BI and Looker deployment pipelines and promote content across environments Microsoft Fabric Platform
• Establish and maintain Microsoft Fabric architecture, including: • Lakehouse and/or Warehouse • Dataflows Gen2 • OneLake data organization
• Manage Fabric capacities, workspaces, and permissions • Monitor performance, cost, and reliability of Fabric workloads • Develop and maintain Python-based data transformations and notebooks within Fabric • Use Python for data preparation, enrichment, validation, and advanced analytics • Define and enforce data modeling and medallion architecture standards Automation & Applications
• Build and maintain automation flows for business processes, approvals, and integrations • Work with Dataverse, connectors, and security roles • Implement error handling, logging, and operational support patterns Platform Governance & Operations
• Define Dev/Test/Prod environment strategy for reporting and automation platform • Implement Application Life best practices (solutions, pipelines, source control where applicable) • Establish governance standards to prevent platform sprawl • Partner with security and IT teams on access control and compliance • Provide guidance and enablement to analysts and citizen developers Collaboration & Leadership
• Translate business requirements into scalable technical solutions • Contribute to platform roadmap and continuous improvement efforts Agentic AI & ML Enablement
• Design and deliver agentic AI solutions that automate multi-step business workflows (tool use, planning, and human-in-the-loop approvals) using enterprise data and governed actions.
• Build RAG (retrieval-augmented generation) patterns over Fabric/OneLake (document ingestion, chunking, embeddings, retrieval evaluation) to power analytics copilots and self-service Q&A.
• Develop and operate ML pipelines (feature engineering, training, evaluation, batch/real-time inference) using Python and approved ML frameworks.
• Establish LLMOps/ModelOps practices: prompt/version control, offline evaluation, regression testing, monitoring (quality, drift, cost, latency), and safe rollback.
• Implement AI security and governance: data access controls, prompt/data leakage prevention, PII handling, model risk reviews, and audit logging for agent actions.
• Partner with stakeholders to identify high-value use cases and deliver measurable outcomes (time saved, defect reduction, SLA improvements).
Required Qualifications
• 5+ years of experience in analytics, BI, or data engineering roles • 3+ years of hands-on Power BI development experience • Strong experience with Microsoft Fabric (Lakehouse, Warehouse, Dataflows) • Proficient in DAX, SQL, and data modeling • Hands-on experience with: • Power Automate (cloud flows, approvals, integrations) • Power Apps (Canvas apps) • Dataverse
• Hands-on Python experience delivering ML or GenAI solutions in production (notebooks-to-service, APIs, scheduled jobs, or integrated automations). • Working knowledge of RAG concepts (embeddings, vector search, retrieval, grounding, evaluation).
• Experience implementing monitoring and testing for data/ML/GenAI systems (data quality checks, model/prompt evaluation, logging/telemetry).
• Experience managing environments, security, and deployments • Strong understanding of data governance and analytics best practices Preferred Qualifications
• Experience designing enterprise-scale analytics platforms • Familiarity with Azure services (Azure SQL, Data Factory, Synapse) • Familiarity with GCP BigQuery and Looker • Experience with CI/CD concepts for Power BI and Looker • Power Platform or Microsoft analytics certifications • Experience working in a Center of Excellence (CoE) model • Experience with Azure OpenAI / Azure AI Foundry (or equivalent) and enterprise deployment patterns. • Experience with orchestration frameworks (e.g., Semantic Kernel, LangChain, Autogen) and tool/function calling.
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