SLSQ227R802 The Global GCP Cloud Alliance, Go-To-Market Strategy & Business Development team owns these three domains with one of our most strategic cloud partners. Reporting to the Global VP, Databricks on GCP Business Unit, and Go-To-Market Strategy & Business Development will recruit, hire and lead a team of highly talented individuals that are obsessed with helping data teams solve the world’s toughest problems with Databricks on GCP. The impact you and your team will have: Design, launch, and scale a comprehensive Databricks on GCP Go-To-Market strategy that accelerates customer business outcomes, grows Databricks consumption, and increases long-term commitments to our lakehouse platform. Define, build, execute and measure the ongoing performance of joint horizontal and industry vertical sales plays with Databricks, GCP, and C&SI Partners to unlock new sales opportunities. Enhance Databricks’ strategic relationship with GCP leaders and executives across product, sales, solution architecture, business development, and partner teams. Motivate GCP sales teams to adopt the Databricks Lakehouse paradigm for our mutual customers' most essential Data and AI initiatives. Unlock value for Databricks, GCP and our mutual customers by identifying, prioritizing and facilitating high value product integrations with GCP services Strengthen the Databricks & GCP alliance by accelerating GCP Partner Program and GCP Marketplace innovations Build a foundation for future growth to help us scale Databricks What we look for: 15+ years of experience in business development, enterprise sales, go-to-market strategy, consulting and product management with companies that are focused on SaaS, cloud computing, analytics, machine learning, artificial intelligence or similar technologies. 5+ years of experience building and leading high-functioning teams and delivering results through others 3+ years of GCP or extended ecosystem experience Ability to attract,
Role overview
Job description
We are looking for a hands-on VP, Product Analytics to lead Product Analytics and build an AI-native analytics operating system across the company’s crypto, stocks, prediction markets, perpetuals, and stock futures products.
You will set the analytics strategy, lead and develop the Product Analytics team, and ensure data consistently shapes product and business decisions. This is a player-coach role: you will operate at executive level while remaining technically close enough to review PRs, guide data modeling and pipeline design, and challenge analytical conclusions.
You will own product and business reporting, experimentation, release measurement, diagnostic analysis, the Amplitude data stack, and the systems through which analytics work is delivered at scale.
Set the vision, priorities, operating model, and quality standards for Product Analytics.
Hire, coach, and develop a high-performing team.
Review analytical and data-engineering PRs, providing guidance on SQL, data models, pipelines, metric definitions, and methodology.
Represent Product Analytics in executive and product decision-making.
Allocate team capacity toward the company’s highest-impact opportunities.
Design how analytics work moves from business questions to trusted decisions across intake, data discovery, analysis, validation, reporting, and knowledge management.
Build reusable AI tools to automate repetitive workflows, encode analytical standards, and improve the speed, quality, and consistency of delivery.
Establish appropriate governance, validation, and human review for high-stakes decisions.
Measure the system’s impact on turnaround time, analytical quality, experimentation throughput, and team capacity.
Establish trusted KPIs, source-of-truth metrics, dashboards, and executive business reviews.
Ensure reporting is accurate, consistent, and focused on decisions—not simply monitoring performance.
Partner with Product, Engineering, Data, CRM, Growth, and other functions to align definitions, priorities, and business interpretation.
Make experimentation and evidence core parts of product development.
Establish standards for hypotheses, success metrics, guardrails, experiment design, causal interpretation, and rollout decisions.
Use AI and automation to streamline experiment intake, validation, analysis, and readouts while maintaining analytical rigor.
Help product teams move from opinion-led decisions to repeatable test-and-learn practices.
Own the Amplitude data stack, including instrumentation strategy, event taxonomy, governance, data quality, and integration with warehouse reporting.
Set standards for product instrumentation and ensure new releases can be measured reliably.
Set standards for and review analytical models and pipelines, ensuring metrics remain traceable, reproducible, and trusted as products evolve.
Lead diagnostic deep-dives into activation, conversion, retention, user behavior, market liquidity, trading execution performance, and product health.
Define measurement frameworks and success criteria for major product launches.
Oversee post-release evaluations that inform whether the company should iterate, scale, or stop.
Identify root causes, challenge weak hypotheses, and translate complex findings into clear recommendations and product actions.
Leadership operates from trusted, consistent product and business metrics.
The Product Analytics team has clear priorities, strong technical standards, and consistently high-quality output.
AI-enabled workflows materially improve analytical speed, quality, and capacity.
Product teams use experimentation and evidence as standard parts of development.
Amplitude instrumentation and taxonomy are reliable, governed, and useful.
Major product launches have clear success criteria and rigorous post-release evaluation.
High-impact analyses lead to concrete product, operational, and business decisions.
Proven experience leading Product Analytics teams in a complex, fast-moving organization.
Strong hands-on technical judgment, advanced SQL, and experience with modern data platforms such as Databricks.
Demonstrated experience using AI to redesign analytics operations—not merely improve individual productivity.
Ability to design and implement AI-enabled workflows, reusable agents or tools, validation controls, and analytics knowledge systems.
Experience owning a product analytics platform; deep Amplitude experience is strongly preferred.
Strong knowledge of experimentation, causal inference, product measurement, and diagnostic analysis.
Ability to turn ambiguous business questions into rigorous analysis and clear decisions.
Strong product judgment, people leadership, and executive communication skills.
Consumer fintech, trading, marketplaces, or other transaction-heavy products.
Exchange mechanics, market liquidity, and experience with multi-asset products.
Leading company-wide adoption of new analytics technologies and ways of working.
What they are looking for
Skills & requirements
Department · Product Management & Product Design
Hiring company
Crypto.com
View the company profile, current openings and hiring details.
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