Principal, Value Management

Cloudera
4 LocationsPosted 19 March 2026

Tech Stack

Job Description

Business Area: Corp. Strategy Seniority Level: Mid-Senior level Job Description: At Cloudera, we empower people to transform complex data into clear and actionable insights. With as much data under management as the hyperscalers, we're the preferred data partner for the top companies in almost every industry. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world’s largest enterprises. As a Principal in Business Value Management, you operate at the intersection of business value, AI platform architectures, and deal strategy. You partner with account teams and customer executives to translate complex data and AI capabilities into quantified economic outcomes, shaping investment decisions, influencing deal structures, and enabling enterprises to transition toward AI-native operating models. As the Principal in Business Value Management you will: Drive ARR growth by embedding quantified, forward-looking value narratives into deal strategy, linking AI platform architectures and emerging AI operating models to revenue uplift, cost optimisation, and risk reduction. Build and present CFO-grade business cases (TCO, ROI, NPV, IRR), incorporating evolving cost dynamics such as inference workloads, utilisation patterns, and long-term AI operating economics. Align solution design with commercial objectives by partnering with Sales, Solutions Engineering, and Product, ensuring architectures are optimised for performance, scalability, and durable economic efficiency in AI-driven environments. Engage C-suite stakeholders to shape enterprise AI and data strategies, positioning Cloudera within broader shifts toward platform consolidation, hybrid architectures, and AI-enabled business models. Lead value discovery engagements to map current-state environments to future-state AI-native architectures, with explicit quantification of value drivers, investment trade-offs, and execution pathways. Leverage AI tools and automation, including LLMs and agentic workflows, to scale analysis, accelerate insight generation, and industrialise repeatable assets such as TCO models and scenario simulators. Support complex, multi-year deal cycles through commercial structuring, scenario modelling, and competitive positioning against cloud-native and emerging AI platform alternatives. Represent Cloudera in executive forums, articulating perspectives on enterprise AI economics, architectural trade-offs, and the long-term implications of AI adoption on cost structures and operating models. We’re excited about you if you have: (Minimum Qualifications): 5–7+ years in strategy consulting, value engineering, or equivalent customer-facing roles Strong commercial and financial acumen, including advanced financial modelling (DCF, NPV, IRR) and the ability to link technology decisions to P&L, balance sheet, and cash flow outcomes Demonstrated ability to influence enterprise deal cycles, including shaping deal strategy, positioning, and commercial outcomes Solid understanding of modern data platforms, distributed systems, and AI/ML workloads, including data pipelines, model deployment, and infrastructure trade-offs Ability to quantitatively reason about evolving cost drivers in AI and data environments, including compute, storage, and workload patterns Hands-on experience using AI tools (e.g., LLMs, automation frameworks) to support analysis, modelling, and content generation Strong executive presence with the ability to engage and influence CIO, CFO, CDO, and senior business stakeholders Excellent communication skills, with the ability to distil complex technical and financial concepts into clear, actionable insights High ownership mindset, with the ability to operate independently in ambiguous, high-growth environments Proven experience working closely with Sales teams in complex, high-value enterprise deals You may also have: (Preferred Qualifications): Post-MBA experience, particularly within a top-tier m ... (truncated, view full listing at source)
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