Senior Marketing Operations Analyst

Smarsh•US - Remote, OR

20d

About The Position

Smarsh is seeking a senior marketing analytics professional to build and own the data foundation used by marketing and go-to-market teams, including the governed data models and semantic layer that support reporting and AI-assisted analysis. The role sets the marketing measurement and data roadmap and partners with Marketing Operations, Demand Generation, Sales/Revenue Operations, Customer Success, IT/Data Architecture, and marketing and GTM leadership on planning, pipeline, and growth strategy. The position owns marketing data architecture from source-system connectors and ingestion into Snowflake through transformations, orchestration, and curated models. It also leads marketing attribution and ABM measurement, develops analysis and executive dashboards, governs shared metric definitions, and establishes data quality, privacy, security, and governance practices. The analyst will support self-service AI tools, validate data and AI-generated answers, and mentor colleagues in analytics tools and responsible AI use.

Requirements

At least 5 years of experience in GTM, marketing, or revenue operations analytics, or business intelligence; B2B SaaS or technology experience is ideal.
Advanced SQL skills and hands-on experience with Snowflake or a comparable cloud data warehouse, including designing data models.
Hands-on experience building production-grade, tested, and documented dbt models.
Experience building or governing a semantic or metrics layer, such as dbt Semantic Layer, LookML, Omni, or a BI-native equivalent.
Experience with ELT and orchestration tools such as Fivetran, Airflow, or similar.
Deep working knowledge of Salesforce data structures, including leads, contacts, accounts, opportunities, campaigns, and campaign members, and Marketo or a comparable marketing automation platform.
Expertise in at least one major BI platform, such as Power BI, Looker, Tableau, Omni, or Hex, including governed self-service dashboard design.
Proven experience designing and governing multi-touch attribution and ABM reporting, and explaining methodology and limitations to non-technical executives.
Practical, hands-on use of AI tools in analytics work and a clear perspective on what makes data AI-ready.
Track record of owning an analytics roadmap and influencing senior stakeholders with data.
Excellent written and verbal communication skills, including the ability to turn complex analysis into a concise business narrative.

Nice To Haves

Experience building or evaluating AI agents or LLM-based assistants that answer business questions over a governed data model, including accuracy testing.
Python or R skills for statistical analysis, automation, or modeling, such as forecasting, propensity, marketing mix, or incrementality analysis.
Experience with Marketo Measure (Bizible) at an administrator or model-design level.
Familiarity with sales engagement and conversation intelligence platforms, data enrichment and hygiene tools, ABM/intent platforms, and product analytics tools.
Experience supporting annual planning, territory design, pipeline coverage modeling, or retention KPIs.
Experience in a regulated industry, such as financial services or healthcare, where data accuracy and auditability are especially important.
Bachelor's degree in Analytics, Statistics, Computer Science, Business, Marketing, or a related field, or equivalent practical experience.

Responsibilities

Design and build a governed, AI-ready marketing and GTM data foundation, including dbt models and a semantic layer with consistent metric definitions.
Prioritize data-foundation domains with RevOps and IT, beginning with marketing performance and attribution and connecting to pipeline, account hierarchy, and customer-retention data.
Build validation and testing frameworks, including data tests, reconciliation checks, and accuracy evaluation of AI-generated answers.
Partner with Marketing Operations and IT to deploy and improve AI tools that provide self-service answers to recurring marketing and pipeline questions.
Own the marketing data architecture, including source-system connectors, Snowflake ingestion, transformation logic, orchestration, and curated data models.
Build and maintain reliable data pipelines for systems such as Salesforce, Marketo, Marketo Measure/Bizible, ABM, advertising platforms, and sales-engagement platforms, with monitoring and documented SLAs.
Model account hierarchies and lead-to-account matching so marketing engagement rolls up appropriately to accounts, buying groups, and opportunities.
Design, govern, and evolve marketing attribution models, including W-Shaped, Custom Model, and account-level influence, documenting assumptions and limitations.
Lead ABM measurement, including account engagement scoring, buying-group coverage, intent-to-pipeline conversion, and target-account progression.
Use cohort analysis, funnel velocity, incrementality or test-and-control design, and forecasting to evaluate performance and recommend next steps.
Analyze campaign and channel performance and provide prioritized recommendations on budgets and program mix.
Partner with marketing and GTM leadership on annual planning, pipeline targets and coverage, growth strategy, and operating cadences.
Build and own executive-grade dashboards reconciled against Salesforce and finance data; own analytics for monthly and quarterly business reviews and QBRs.
Define and govern shared marketing metric definitions, including MQL/MQA, SAL, sourced versus influenced pipeline, CAC, and ROI, and drive adoption across Marketing, Sales, and Customer Success.
Set and maintain the marketing analytics roadmap, prioritizing requests, balancing ad hoc work with foundational builds, and communicating trade-offs.
Establish data quality standards and automated checks across CRM, marketing automation, and the warehouse; address root causes of data issues.
Ensure marketing data and AI use align with company privacy, security, and governance requirements in partnership with Legal, Security, and IT.
Mentor analysts and Marketing Operations teammates in SQL, dbt, data modeling, and responsible use of AI in analytics.