Data analyst V

Data Analyst V

Company's 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.

Typical Day-to-Day in the role:
Work directly with Marketing, Sales, and partner teams to shape and influence audience strategy
Run audience, lifecycle, funnel, and churn analysis and size the revenue opportunity behind each segment
Meet with Data Scientists and Data Engineers to define business logic and improve the underlying data infrastructure
Share insights and recommendations with business stakeholders and senior leadership
Split roughly 30% hands-on coding/technical work and 70% cross-functional communication

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
8+ 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

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

Nice-to-have Skills:
Pipeline building with dbt, Airflow, or equivalent orchestration, plus reporting/BI in a Company s 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

Years of overall experience required:
8+ years of experience in marketing analytics, data engineering, data science, or a related analytics role

Degrees/certifications required:
Bachelor's degree in a quantitative, technical, or business field, or equivalent practical experience

Disqualifiers:
Profiles that are purely dashboard/reporting execution without ownership of analysis methodology, or purely consumer/ads-side analytics with no B2B or CRM data exposure, are likely not the right fit. Candidates who cannot write advanced SQL independently should be screened out

Interviews:
1 round- intro + technical (30 min) - 15min intro - 15min SQL coding interview
2 round- case interview (30 min) - business case to test their analytics ability - 30min