AI Data Engineer & Analyst

Job Description

Key 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
• Partner with an external Microsoft-certified consultancy providing end-to-end project support, from strategy and infrastructure planning through to technical execution, leveraging their specialist Microsoft expertise to accelerate delivery, validate architectural decisions, and ensure best-practice implementation across the full Microsoft stack
• 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

Experience:

• 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

Are you interested in this position?
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