Global GTM Practice Architect for Agentic Data Cloud within Google Cloud, responsible for owning global strategy and business goals, driving GTM motion, and partnering with cross‑functional teams.
As an Agentic Data Cloud Sales Specialist, you will be at the forefront of driving Google Cloud's most critical data and AI growth. You will drive growth by securing net-new greenfield logos and identify untapped, uncommitted workloads. You will partner with field sales representatives, customer engineers, and partners to execute joint Data+AI plays that establish long-term data platform standardization.
Responsibilities
Deliver against quota and achieve or exceed business and growth goals.
Drive net-new greenfield logos and workloads in existing accounts through proactive campaigns.
Run complex, multi-threaded business cycles from initial discovery and value hypothesis to Return on Investment (ROI) business case creation and commercial close.
Engage business leaders, Chief Data Officer, Chief Financial Officer, Chief Marketing Officer, Chief AI Officer, through value-selling, tying modern data and AI capabilities to quantified business outcomes.
Align cross-functionally with Field Sales Representatives (FSRs) and partners to execute joint Data+AI plays, driving platform standardization and co-sell motions.
Requirements
Bachelor's degree or equivalent practical experience
As a Forward Deployed Engineer (FDE) on our Data Cloud team, you will be an embedded builder who bridges the gap between frontier data solutions and production-grade reality for customers. You will function as an innovator-builder, working directly within customer's environments to move data and machine learning workloads from idea to production on Google Cloud.
Responsibilities
Build and ship production data and machine learning workloads with customers, writing, testing, and performance-tuning PySpark, SQL and Python on BigQuery, Managed Spark, Spanner and AlloyDB.
Stand up working proofs with customer's data, including de-identifying sensitive data (e.g., Payment Card Information (PCI), Protected Health Information (PHI)).
Build the data foundation for agentic solutions, including lakehouse architectures, metadata and semantic context, and the access controls that let custom agents act on trusted data.
Train, evaluate, and deploy machine learning and agentic components where they improve the customer’s business metric, with evaluation and monitoring in place.
Migrate high-cost analytics, Spark and operational database workloads from other platforms onto Google Cloud engines, with measured price-performance results.
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