How will you make a difference to PMI?
The Manager, Marketing Data and Analytics owns the business data architecture and metric definitions behind Marketing's numbers, and leads the team that measures Marketing. The role defines how marketing, customer, product, and revenue data should be modeled, decides what each metric means, and ensures those definitions are implemented consistently across Snowflake, BI, and natural-language analytics.
The role combines hands-on technical depth with team leadership. The individual is expected to be advanced in SQL, to design analytical data models, and to profile, reconcile, and diagnose data directly, so they can specify what engineering builds and verify that the result represents the business correctly. They are equally expected to lead three to four analysts, set the standards those analysts work to, and develop the team's technical capability.
Data Engineering and the Snowflake team own ingestion, infrastructure, orchestration, transformation pipelines, and semantic view implementation. This role represents Marketing in the design of the data layer, writes the specifications those teams build against, and is accountable for ensuring the resulting data products correctly represent the business.
What you’ll bring to the role:
Business Data Architecture, Metric Definitions, and Context
Own Marketing's canonical metric definitions and the business logic the governed semantic layer implements, and arbitrate those definitions when marketing, finance, and reporting platforms disagree.
Specify the semantic models for the most complex and cross-domain marketing use cases, and validate what the Snowflake team builds against that specification.
Own the business data architecture for Marketing, defining the facts, dimensions, grain, relationships, hierarchies, and conformed dimensions that connect marketing, customer, product, transaction, and engagement data.
Design analytical models that answer cross-domain questions spanning acquisition, engagement, conversion, certification, membership, renewal, and revenue.
Write advanced SQL to profile data, validate sources, reconcile metrics, build reusable datasets, and investigate complex customer and business questions.
Determine what unstructured content, such as business documentation, definitions, and prior analyses, must be retrievable alongside structured metrics for natural-language and agent-based analysis, and maintain source-to-metric mappings and lineage.
Own the business questions, expected results, and synonym glossary behind the Verified Query Repository supporting Cortex Analyst and natural-language analytics.
Own the context layer that makes Marketing's data interpretable to analysts and AI agents, including entity descriptions, metric documentation, approved analytical uses, and known limitations of each source.
Diagnose discrepancies across Snowflake, BI, Adobe Analytics, marketing platforms, finance reporting, and operational systems.
Identify gaps in source data, identity resolution, event structures, and dimensional consistency before they become downstream reporting issues.
Define ownership boundaries between source systems, engineered data products, semantic models, and reporting layers.
Team Leadership and Capability
Lead, coach, and develop a team of three to four analysts spanning paid media, customer and lifecycle analytics, and digital analytics.
Set the Marketing Analytics roadmap, allocate the team against it, and manage intake and prioritization from across Marketing.
Establish and enforce analytical standards including SQL quality, peer review, testing, documentation, and reuse.
Review the team's models, queries, and analyses before they reach stakeholders, and hold the quality bar for what gets published.
Grow the team's depth in dimensional modeling, data modeling practice, and analytical rigor through direct coaching and review.
Manage performance, hiring, and development planning for the team.
Marketing Measurement…