Senior Marketing Analyst, Audience Strategy & Insights

Start/End Dates: 11/2/2026 - 11/1/2027
Hybrid, SF, NYC or MPK
Job Title: Data Analytics & Engineering - Data Analyst V

Job Description: Senior Marketing Analyst, Audience Strategy & Insights

Business Messaging Marketing team is seeking a Senior Marketing Analyst who is both technically deep and business minded. This role uses expert SQL and large, complex datasets to drive audience segmentation, audience strategy, and revenue opportunity sizing, and translates that analysis into recommendations that shape business, product, and investment decisions. The ideal candidate is comfortable partnering with Data Scientists and Data Engineers to define the data logic and pipelines behind audience and reporting systems and has a track record of influencing senior leadership with clear, quantified insights.

Must-Have Skills
Expert SQL on large datasets — complex queries, CTEs, window functions, and query optimization against millions of records, including reconciling multi-source data and root-causing discrepancies
End-to-end audience/customer analysis — segmentation, lifecycle and funnel analysis, revenue opportunity sizing, and quantitative business cases with assumptions clearly stated; hands-on with a CDP (preferably Salesforce Data Cloud) to build and activate segments
Stakeholder communication and influence — translating complex data into clear direction and recommendations for XFN Marketing, Sales, and partner teams, and presenting to senior leadership
Pipeline building with dbt, Airflow, or equivalent orchestration, plus reporting/BI in environment (Hive, Unidash) or equivalent
Salesforce Marketing Cloud and marketing automation workflows; fluency with CRM and account-level data models
Statistical modeling (propensity, LTV, attribution, forecasting, experiment design) and basic Python for automation and API work.

Responsibilities
- Deliver deep audience analysis, including segmentation, lifecycle and funnel analysis, growth and churn signals, and revenue and adoption attribution. Size revenue opportunities and build the business case for which audiences to prioritize
- Define how a business question should be answered, including what to measure, the methodology to use, and which assumptions apply
- Pull, clean, and analyze large datasets (millions of records) using advanced SQL. Reconcile data across sources and root-cause discrepancies before they reach reporting
- Partner with Data Scientists and Data Engineers to define business logic, data models, and pipelines, and validate what is built
- Build automated reporting and self-service dashboards for recurring business needs
- Translate audience definitions into campaign-ready segments and signals in partnership with campaign and lifecycle owners
- Present findings and recommendations to senior leadership and cross-functional partners

Minimum Qualifications
- 7+ years in marketing analytics, data science, or business analytics, and a Bachelor's degree in a quantitative, technical, or business field, or equivalent
- Expert-level SQL, including complex queries, CTEs, window functions, and query optimization across datasets of millions of records
- Proven track record of owning audience or customer analysis end-to-end: segmentation, revenue opportunity sizing, and quantitative business cases, with assumptions and limitations clearly articulated
- Demonstrated ability to partner with Data Scientists and Data Engineers to define business logic and build data pipelines, manage complex multi-source data across CRM, product, engagement, and third-party sources, and stand up automated reporting and dashboards (e.g., Tableau)
- Background in B2B marketing, sales, or customer analytics, with a history of presenting to and influencing senior leadership on business or product decisions, and communication that lands with both technical and non-technical audiences

Preferred Qualifications
- Hands-on pipeline building with dbt, Airflow, or equivalent orchestration tools
- Familiarity with Hive and Unidash, or comparable large-scale query and dashboarding environments
- Working knowledge of a customer data platform, preferably Salesforce Data Cloud, including segment creation, Calculated Insights, and activation
- Exposure to Salesforce Marketing Cloud and marketing automation workflows
- Statistical modeling across propensity, LTV, attribution, forecasting, and experiment design
- Fluency with CRM and account-level data models
- Advanced Google Sheets/Excel, including pivot tables, lookups, and complex formulas
- Basic Python for automation and API utilization