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

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As an Associate Partner in the Tech Industry Data & AI team at a leading consulting firm based in New York, you will lead complex engagements for semiconductor clients, driving both go-to-market growth and large-scale delivery execution. Your day-to-day responsibilities include shaping enterprise data strategies, designing modern data ecosystems, and delivering end-to-end solutions across advanced analytics, AI/GenAI/Agentic AI, MES, and cloud-native platforms. You will leverage your deep expertise in technologies such as distributed data processing, real-time streaming architectures, and ML lifecycle management to architect scalable data platforms and AI solutions. With a strong background in the semiconductor industry, you will mentor high-performing technical teams and ensure robust governance frameworks for trusted data foundations across regulated operations.

Skills

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

What you'll do

Lead complex Data & AI programs for semiconductor clients.
Shape enterprise data strategies and AI adoption roadmaps.
Architect modern data ecosystems including cloud-native platforms.
Design and implement large-scale data engineering pipelines.
Ensure robust governance, security, and compliance in data projects.
Deliver SiView MES implementations with strategic oversight.
Mentor technical teams in Data Engineering and MLOps disciplines.

What we're looking for

15+ years of experience in Data, Analytics, AI/GenAI/Agentic AI, and enterprise technology leadership.
Strong semiconductor industry expertise with deep understanding of data and AI use cases.
Deep knowledge of modern Data & AI platforms including advanced analytics and complex data modeling.
Hands-on experience in large-scale data engineering and real-time streaming architectures.
Proven ability to combine technical depth with client-facing leadership for strategic enterprise clients.
Experience designing cloud-native data platforms and hybrid/multi-cloud architectures.

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