Analytics GGS Senior Analyst

Salesforce•Seattle, WA

1d•$94,000 - $142,300

About The Position

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. 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.

Requirements

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.
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.

Nice To Haves

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.

Responsibilities

Design, build, and maintain Tableau dashboards and always-on reporting for demand gen KPIs, diagnostic metrics, and leading indicators.
Ensure reporting stays accurate and current, proactively catching and resolving data issues or anomalies.
Serve as the primary builder in partnership with the Sr. Manager - translating measurement frameworks and KPI definitions into working dashboards and reports.
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.
Identify and monitor diagnostic/leading indicators that help flag performance shifts before they show up in lagging KPIs.
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.
Partner with other analysts, data science, and data engineering teams to source data, resolve data quality issues, and align on reporting logic.
Work with the Sr. Manager to turn metric and measurement designs into concrete queries, data models, and dashboard specs.