AI Data Engineer & Analyst

About the role

We are seeking a highly skilled AI Data Engineer & Analyst to lead the design and implementation of an AI-powered strategic account intelligence platform. This is a greenfield build within the Microsoft ecosystem (Microsoft Fabric, OneLake, Azure AI, Power BI, Purview, Entra ID), delivering an end-to-end solution from data ingestion and semantic modeling through to AI-driven recommendations and executive-ready dashboards. This role is ideal for a hands-on technical professional who thrives at the intersection of data engineering, machine learning, and business intelligence - someone who can architect a robust data platform and bring it to life with actionable AI-powered insights. You will work in close partnership with an external Microsoft-certified consultancy engaged to support the full project rollout. The consultancy will provide expert guidance and hands-on support across all project phases, from strategy and planning through infrastructure evaluation and technical execution, ensuring the platform is built to enterprise standards and aligned with Microsoft best practices.

Responsibilities

• Data Architecture & Engineering (40%)
• Design and implement the canonical object model in Microsoft Fabric / OneLake (Lakehouse / Data Warehouse)
• Build and maintain automated ingestion pipelines using Data Factory in Fabric / Azure Data Factory
• Implement identity resolution across disparate source systems (deterministic matching on shared keys + probabilistic/ML-based entity resolution)
• Create golden records with source-confidence scoring per attribute and conflict resolution rules
• Ensure schema validation, data quality checks, and attribute-level completeness thresholds across all pipelines
• Design for scalability to hundreds of accounts with near-real-time query performance
• AI / Machine Learning (30%)
• Develop the opportunity scoring model using Azure AI Services / Azure Machine Learning / Fabric Data Science
• Build NLP-based news signal classification and entity extraction from external feeds
• Implement the NBA recommendation engine with explainable evidence chains linking scores to underlying data points, signals, and model factors
• Design and implement decision-lineage capture and the continuous learning feedback loop
• Produce ranked recommendations with confidence intervals
• Plan for quarterly model review cycles assessing recommendation quality, bias, and drift
• Business Intelligence & Visualization (20%)
• Develop interactive Power BI dashboards in Direct Lake mode over OneLake
• Build account-level opportunity score dashboards with drill-through to evidence chains
• Create tracking and reporting dashboards for recommendation outcomes, acceptance rates, pipeline impact, and model performance
• Generate auto-formatted sales-ready outputs (one-page account briefs, exec summaries, talking points)
• Governance, Security & Collaboration (10%)
• Implement Role-Based Access Control (RBAC) via Microsoft Entra ID with object-level permissions
• Configure data lineage tracking through Microsoft Purview (Data Map, Unified Catalog)
• Ensure full audit logging of data access, recommendation generation, and user actions
• Collaborate with business stakeholders (Account Directors, Sales Leaders, Strategic Planning teams) to validate data models, refine scoring logic, and iterate on outputs
• Document architecture decisions, data flows, and operational runbooks
• Required Qualifications
• Bachelor's degree in Computer Science, Data Science, Information Systems, Statistics, or a related technical field

Requirements

• 5+ years of professional experience in data engineering, data analytics, or business intelligence
• 3+ years working within the Microsoft data ecosystem (Azure / Fabric / Power BI)
• Demonstrated experience building end-to-end data platforms from ingestion through modeling to dashboards
• Proven track record with AI/ML model development and deployment in a production or near-production environment
• Experience with entity resolution / identity matching across multiple data sources
• Technical Skills (Required):
• Data Platform
• Microsoft Fabric (OneLake, Lakehouse, Data Warehouse, Data Factory, Fabric Data Science)
• AI / ML
• Azure AI Services, Azure Machine Learning, model training & scoring pipelines
• BI & Dashboards
• Power BI (Direct Lake mode, DAX, advanced data modeling, report design)
• Data Governance
• Microsoft Purview (Data Map, Unified Catalog, Lineage), source-confidence scoring
• Identity & Access
• Microsoft Entra ID (RBAC, object-level permissions)
• Programming
• Python (pandas, scikit-learn, or equivalent ML frameworks), SQL (T-SQL / Spark SQL

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