Analytics GGS Senior Analyst

Momentum
Momentum

IT, Data Science

Seattle, WA, USA

Posted on Oct 8, 2026

We are seeking a highly technical and detail-oriented Sr. Analyst, Demand Generation Analytics to serve as the primary hands-on executor for digital demand generation reporting and analysis across multiple Salesforce products and lines of business. This role spans website, email, paid media, account-based marketing (ABM), and other program-driven demand gen initiatives. The Sr. Analyst partners closely with the Sr. Manager, Demand Generation Analytics & Performance and reports directly to the hiring manager, building and maintaining the always-on reporting, dashboards, and ad-hoc analysis that power the team's KPIs and diagnostic/leading indicators.

This individual is the builder: extremely proficient in SQL and highly fluent in Tableau, comfortable navigating complex data sources independently to answer questions quickly and maintain reliable, always-on reporting. They will partner cross-functionally between business function leaders, other analysts, data science, and data engineering groups to get their work done.

Key Responsibilities

Always-On Reporting & Dashboarding

  • Dashboard Build & Maintenance: Design, build, and maintain Tableau dashboards and always-on reporting for demand gen KPIs, diagnostic metrics, and leading indicators.

  • Reporting Reliability: Ensure reporting stays accurate and current, proactively catching and resolving data issues or anomalies.

  • Execution Partnership: Serve as the primary builder in partnership with the Sr. Manager - translating measurement frameworks and KPI definitions into working dashboards and reports.

Ad-Hoc & Diagnostic Analysis

  • Ad-Hoc Analysis: Perform ad-hoc, deep-dive analysis on demand gen performance questions as they come up, using SQL to independently query and join across data sources.

  • Leading Indicator Tracking: Identify and monitor diagnostic/leading indicators that help flag performance shifts before they show up in lagging KPIs.

  • Data Navigation: Navigate across Google Analytics (in Snowflake), Salesforce CRM objects (Campaigns, Leads, Contacts, Accounts, Opportunities), and paid media platform data to pull, join, and validate data for reporting and analysis.

Cross-Functional Execution

  • Cross-Team Collaboration: Partner with other analysts, data science, and data engineering teams to source data, resolve data quality issues, and align on reporting logic.

  • Technical Translation: Work with the Sr. Manager to turn metric and measurement designs into concrete queries, data models, and dashboard specs.

Candidate Requirements and Competencies

Experience & Technical Skills

  • 3+ years of experience in Marketing/Demand Gen Analytics, Business Intelligence, or a highly quantitative field, ideally in B2B SaaS or technology.

  • Strong proficiency in SQL - able to independently write complex queries and joins across large data sets (Snowflake or similar cloud data warehouse).

  • Highly proficient in Tableau - able to build and maintain dashboards from scratch, not just modify existing ones.

  • Familiarity with digital marketing data sources: Google Analytics/website reporting data, Salesforce CRM objects (Campaign, Lead, Contact, Account, Opportunity), and paid media platform data.

  • Comfortable performing ad-hoc analysis under time pressure and communicating findings clearly.

Communication & Collaboration

  • Strong written and verbal communication skills, particularly for explaining technical/data findings to non-technical partners.

  • Effective collaborator who can work cross-functionally with analysts, data science, and data engineering teams to get work done.

  • Detail-oriented and reliable - comfortable owning always-on reporting that others depend on.

Preferred Qualifications

  • Working knowledge of additional analytical languages/tools such as Python, R, or dbt.

  • Exposure to demand gen or digital marketing channels (email, paid, web, ABM) - helpful for context, though deep strategic experience is not required.

  • Experience partnering with data engineering or data science teams on data quality or pipeline issues.