The RoleProofpoint is building a single, governed analytical foundation for the company at a moment when it matters most: a Snowflake platform consolidation is underway, a transformative acquisition is signed and pending, and the company is moving toward AI-native analytics. The business definitions already exist and are Finance-approved. What's missing is the durable, auditable, machine-readable layer that lets dashboards, self-service tools, and AI agents all give the same answer. You will build it.
You own the analytical and semantic layer in Snowflake: governed data models, metric logic, and the context that sits between raw data and business consumers. IT and Data Engineering own ingestion and upstream pipelines. You partner with them to establish the analytical requirements, interfaces, validation standards, and data models that enable consistent downstream consumption. You are the technical counterpart to two business-facing pillars and to the Senior Director who owns Proofpoint's ARR/NARR metric definitions. Their recurring questions become your reusable assets. You’ll be expected to understand the business behind the questions, not just the schema behind the data.
This is a senior-level individual contributor role, reporting to the Senior Director, Business Analytics.
Location: This is a hybrid role based in our Sunnyvale, CA HQ, 4 days a week.
Your ResponsibilitiesSemantic Architecture & Governed Data Assets
- Semantic Layer: Design and build governed analytical data models and the semantic layer in Snowflake, translating approved metric definitions (ARR, NARR, retention, customer lifecycle) into reusable, versioned calculation logic.
- Metric & Context Registry: Establish a machine-readable metric and context registry so that business definitions, relationships, and calculations are interpreted consistently across Power BI, self-service tools, and AI-driven interfaces. This does not exist today; you will design it.
- Acquisition Integration: Integrate acquired businesses into the governed metric layer, including entity mapping, definition reconciliation, and historical restatement.
AI-Native Analytics & Business Intelligence
- AI-Native Analytics: Design and implement AI-native analytical capabilities on Snowflake's Cortex ecosystem and governed semantic models, evaluating the architectural approaches that enable reliable natural-language and agent-based access to business information, and recommending how they scale on the platform the company is standardizing on.
- Business Intelligence: Evolve Power BI from fragmented functional reporting toward integrated cross-functional views connecting commercial activity, product performance, and financial outcomes.
Data Quality, Governance & Technical Leadership
- Reliability Controls: Implement reconciliation, validation, lineage, and monitoring controls that make analytical outputs reproducible, traceable, and suitable for financial reporting governance and audit support.
- Technical Standards: Set technical standards and reusable patterns (modeling, dbt usage, testing, documentation) that let analysts and engineering partners build consistently without central bottlenecks.
- Upstream Issue Resolution: Identify upstream data quality and architectural issues and drive resolution with system owners.
What you bring to the teamRequired
- 8+ years in analytics engineering, data engineering, BI, or data architecture, with substantial hands-on ownership of production analytical models.
- Advanced SQL and deep expertise in dimensional and semantic modeling on a modern cloud data platform.
- Experience building enterprise BI and governed self-service reporting at scale.
- Experience implementing governed business metrics, reconciliation controls, and consistent analytical definitions across enterprise reporting environments.
- Demonstrated habit of starting from the business question: you understand what decision a metric supports, what breaks if it’s wrong, and why the definition is what it is, before you decide how to build it. You don’t need to be a finance expert, but you should be the person who asks.
- Track record of leading technical initiatives across teams without formal authority, and of turning ambiguous business requirements into architecture.
- Strong written and verbal communication with both technical and finance/business stakeholders.
Preferred
- Snowflake and Power BI (our current stack) and dbt.
- SaaS or recurring-revenue metrics (ARR, retention, cohorts); the definitions are owned by the team, so you'll be implementing them, not inventing them.
- Hands-on work with semantic layers, metric stores, or context layers built for LLM/agent consumption (Cortex Analyst, dbt Semantic Layer, Cube, or similar). This area is new for everyone; we are looking for transferable depth and demonstrated curiosity, not years of experience.
- Experience integrating acquired-company data into enterprise models.
- Familiarity with CRM, ERP, and financial planning systems as analytical sources.
What success looks like in year one- Core ARR, NARR, and retention metrics are implemented in a governed semantic layer and validated against approved Finance definitions.
- Priority reporting and analytical use cases consume shared, tested data assets rather than bespoke extracts.
- An initial AI-native analytical capability returns consistent, governed answers to a defined set of business questions.
- Integration requirements and mappings for acquired businesses are established, with priority metrics incorporated as integration progresses.
- Manual reconciliation and redundant analytical work measurably decline for the supported use cases.
#LI-AN2
Why Proofpoint?
At Proofpoint, we believe that an exceptional career experience includes a comprehensive compensation and benefits package. Here are just a few reasons you’ll love working with us:
Competitive compensation
Comprehensive benefits
Career success on your terms
Flexible work environment
Annual wellness and community outreach days
Always on recognition for your contributions
Global collaboration and networking opportunities
