Microsoft Data Team Lead

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OtherTeam Lead

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Quick Summary

Key Responsibilities

Provide technical leadership and develop architecture and engineering capability across teams. Guide clients in establishing data foundations required to support advanced analytics, machine learning,

Requirements Summary

Excellent consulting, communication, commercial and people-leadership skills. Track record of leading teams and complex programmes, influencing executives and governing architecture at scale.

Technical Tools

OtherTeam Lead

Responsibilities

~1 min read

→Provide technical leadership and develop architecture and engineering capability across teams.
→Guide clients in establishing data foundations required to support advanced analytics, machine learning, generative AI and agentic architectures
→Advise senior client stakeholders, shape business proposals and estimates, and connect data foundations to analytics, AI and agentic use cases.
→Oversee architectural consistency, quality and strategic alignment across multiple client engagements and delivery programmes
→Define current-state assessments, target architectures, transition roadmaps and architecture principles for enterprise data platforms.
→Lead design across ingestion, lakehouse, warehouse, semantic, master-data, metadata, governance and data-serving capabilities.
→Select fit-for-purpose patterns across Microsoft Fabric, Azure data services, Databricks and the broader enterprise ecosystem, and non-functional design for security, privacy, sovereignty, resiliency, performance, scalability and cost.
→Chair design governance, manage architecture risk and assure delivery across multiple workstreams or programmes.

Requirements

~1 min read

Excellent consulting, communication, commercial and people-leadership skills.
Track record of leading teams and complex programmes, influencing executives and governing architecture at scale.
Extensive experience leading enterprise data architecture and cloud-transformation initiatives within complex, multi-stakeholder environments.
Deep understanding of data modelling, distributed data processing, integration, governance and analytical architecture.
Deep expertise in Microsoft Fabric, Azure data platforms and modern cloud-native architectural patterns

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