Associate Partner - Tech Industry Data & AI

IBM

Remote

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Work type: Remote
Location: Remote
Posted: 41 days ago

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Similar $196k

$142k most similar roles pay here $246k

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About IBM

IBM is a US-based global technology company providing hybrid cloud, AI, consulting, enterprise software, and IT infrastructure products and services.

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Listed pay typically runs $1,000,000–$1,000,000 across 8 roles with salary data.

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TL;DR · Associate Partner - Tech Industry Data & AI

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As an Associate Partner in the Tech Industry Data & AI team, you will lead engagements for semiconductor clients, driving growth through advanced analytics, AI/GenAI/Agentic AI, MES, and modern data platforms. Your role involves advising C-level executives on enterprise data strategies and digital transformation programs while owning end-to-end delivery of complex projects. You will architect modern data ecosystems, manage cross-functional teams, and ensure robust governance frameworks for trusted data foundations. With deep expertise in cloud-native data platforms and large-scale data engineering, you will mentor high-performing technical teams and deliver scalable solutions that address client business challenges within the semiconductor industry's unique context, including wafer fabrication and supply chain analytics.

Skills

AWS Azure Google Cloud Kubernetes MES Python SQL CI/CD Terraform PostgreSQL Snowflake Docker Prometheus Grafana Apache Spark Hadoop GenAI Agentic AI Data Governance

What you'll do

Drive end-to-end delivery of complex Data & AI programs for semiconductor clients.
Shape enterprise data strategies and AI adoption roadmaps aligned with industry priorities.
Architect modern data ecosystems including cloud-native platforms and governed data products.
Lead technical sales and solution development, translating business challenges into scalable solutions.
Establish robust governance frameworks ensuring trusted data foundations for global operations.

What we're looking for

15+ years of experience in Data, Analytics, AI/GenAI/Agentic AI, and enterprise technology leadership.
Deep expertise in modern Data & AI platforms, including advanced analytics and complex data modeling.
Strong semiconductor industry experience with knowledge of data and AI use cases across wafer fabrication and manufacturing operations.
Hands-on knowledge of large-scale data engineering, real-time streaming architectures, and ML lifecycle management.
Experience designing cloud-native data platforms and hybrid/multi-cloud architectures in major cloud ecosystems (AWS, Azure, Google Cloud).
Proven ability to combine technical depth with client-facing leadership for strategic enterprise clients.

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