Data & AI Engineer Microsoft Fabric, Experimentation Data & Agent Development

Dice is seeking a highly skilled Data & AI Engineer with strong expertise in Microsoft Fabric, Azure AI Services, data engineering, and AI-powered analytics solutions. The ideal candidate will design and manage scalable experimentation data platforms and develop AI-powered data agents to support enterprise analytics and experimentation workflows.

Responsibilities:

• Design, build, and maintain curated Silver-layer datasets in Microsoft Fabric for experimentation analytics and reporting
• Develop reusable data products including standardized tables and views for dashboards, scorecards, and ad hoc analysis
• Ensure datasets are analysis-ready, cleaned, deduplicated, and semantically aligned
• Conduct gap assessments across experimentation KPIs, telemetry systems, and Silver-layer datasets
• Identify data quality, latency, schema, and join-key issues and recommend remediation strategies
• Improve data models using: Facts and dimensions, Conformance rules, Surrogate keys, Grain optimization
• Conduct workshops with BI, reporting, experimentation, and engineering teams
• Define KPI calculations, attribution logic, governance standards, and refresh SLAs
• Create source-to-target mappings, data dictionaries, validation rules, and technical specifications
• Build and maintain robust data pipelines using: Microsoft Fabric Pipelines, Azure Data Factory (ADF), Telemetry/1DS pipelines
• Implement orchestration, incremental loads, monitoring, and error handling mechanisms
• Validate and reconcile datasets with Adobe Customer Journey Analytics (CJA)
• Build automated validation routines for: Missing data, Duplicate detection, Schema drift, Metric anomaly detection
• Coordinate issue resolution with telemetry and engineering teams
• Design and build AI-powered data agents using: Fabric Data Agents, Copilot, Azure OpenAI
• Enable use cases such as: Automated scorecards, Narrative summaries, Self-service analytics Q&A, Metric definition assistants, Data quality monitoring assistants
• Define AI agent architecture, RBAC security, grounding sources, and evaluation metrics
• Maintain documentation for: Data transformations, Pipeline dependencies, Metric definitions, Validation rules
• Implement best practices for: Naming conventions, Semantic consistency, Versioning, Cost optimization
• Support operational monitoring, troubleshooting, and continuous improvement initiatives

Requirements:

• Strong expertise in Microsoft Fabric
• Strong expertise in Data Engineering
• Strong expertise in Data Modeling
• Strong expertise in Big Data Platforms
• Strong expertise in Data Pipeline Design
• Hands-on experience with PySpark
• Hands-on experience with Azure AI Services
• Hands-on experience with AI/ML Integration
• Hands-on experience with Microsoft Fabric Data Agents
• Hands-on experience with Azure Data Factory (ADF)
• Strong understanding of Clickstream data
• Strong understanding of Customer Analytics
• Strong understanding of Adobe Analytics
• Strong understanding of Adobe Customer Journey Analytics (CJA)
• Strong understanding of Experimentation data platforms
• Experience with Data validation and reconciliation
• Experience with Performance tuning and monitoring
• Experience with Telemetry pipelines
• Experience with Data governance and semantic modeling
• Strong analytical and problem-solving skills
• Ecommerce domain experience preferred
• Experience supporting experimentation and customer analytics platforms
• Strong knowledge of ecommerce and digital analytics ecosystems
• Exposure to AI-driven analytics and self-service data platforms
• Strong collaboration and stakeholder communication skills