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Jade Global

Data & AI GTM Leader

1731 Technology Dr Ste 350, San Jose, CA 95110-1361

Full-time

First seen by offpeak October 24, 2026

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Data & AI GTM Leader1

About the role

Jade Global is hiring a senior Data & AI Go-To-Market Leader to own strategy, commercialization and revenue growth for our Data, Analytics and AI services in the US. This leader will carry a bookings target, build qualified pipeline with Sales, lead data presales, and grow joint business with our ISV partners.

The role sits at the intersection of client advisory and commercial ownership. You will shape offerings, win deals, and turn partner relationships into repeatable revenue across platforms such as Snowflake, Databricks, Boomi and the major cloud hyperscalers.

Key responsibilities

Strategy, commercialization and revenue growth

Solutions and GTM offerings

Technology leadership

GTM motion for Data, Analytics and AI

Data presales

ISV partnership management

Pipeline and revenue ownership

Advisory and deal support

How success is measured

Area

Measure

Revenue

                             Bookings vs. annual target; Data & AI revenue growth (YoY)

Pipeline

                            Qualified pipeline coverage (3x+), win rate, average deal size

Partners

                            Partner-sourced and co-sell pipeline; tier and competency progression

Presales

                            Proposal turnaround, solution reuse, presales-to-win conversion

Accounts

                             New logos; expansion within top accounts

Margin

                             Gross margin on deals shaped

Technical depth expected

This is a technically credible leader, not a pure sales role. You should be able to whiteboard an architecture with a client's chief architect, challenge a partner's solution design, and validate effort estimates without leaning on others.

Area

What you should know well

Data platforms

Lakehouse and warehouse architectures (Snowflake, Databricks, BigQuery, Redshift, Microsoft Fabric/Synapse); medallion design, performance and cost (FinOps) trade-offs

Data engineering & integration

Batch and streaming pipelines (Spark, Kafka, dbt, Airflow), CDC, iPaaS and API-led integration (Boomi, MuleSoft), ERP/CRM data extraction (SAP, Oracle, Salesforce)

Data management & governance

Data modeling, MDM, data quality, catalog and lineage (Unity Catalog, Collibra, Alation), security, privacy and regulatory controls

Analytics & BI

Semantic layers, self-service BI (Power BI, Tableau, Looker), KPI frameworks and embedded analytics

AI/ML & MLOps

ML lifecycle, feature stores, model deployment and monitoring (MLflow, SageMaker, Azure ML, Vertex AI)

Generative & agentic AI

LLMs, RAG, vector databases, prompt and context engineering, AI agents and orchestration frameworks, evaluation and guardrails

Responsible AI

AI governance, model risk, explainability, and compliance with emerging AI regulations

Cloud

Reference architectures on AWS, Azure and GCP; migration and modernization patterns; cost estimation

Expected to:

Qualifications

Required

Preferred

Core competencies

What we offer

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