Responsibilities

• Design, build, and manage a centralized marketing data ecosystem leveraging Snowflake, dbt, data ingestion tools, and BI platforms.
• Develop and maintain enterprise-wide marketing KPIs, including customer acquisition cost, ROAS, conversion metrics, lifetime value, attribution models, and revenue performance metrics.
• Ensure accurate tracking and attribution across paid and owned channels through governance of pixels, server-side tracking, conversion APIs, tag management, and offline conversion integrations.
• Build reporting frameworks and self-service dashboards that allow marketing teams to monitor performance in near real time.
• Partner with marketing leadership to develop forecasting models, performance targets, budget scenarios, and investment recommendations.
• Lead measurement initiatives including incrementality testing, lift studies, geo-testing, and A/B testing programs.
• Identify data quality issues and establish governance processes to improve reporting consistency and reliability.
• Translate complex analytical findings into clear recommendations for both technical and non-technical stakeholders.
• Collaborate with data engineering, finance, and marketing teams to align reporting standards and performance measurement methodologies.

Requirements

• 5+ years of marketing analytics, marketing operations, or performance measurement experience.
• 2+ years of hands-on ownership of a cloud data warehouse environment such as Snowflake.
• Strong experience with dbt and modern data modeling practices.
• Deep understanding of paid search, paid social, affiliate marketing, attribution, and conversion tracking.
• Experience integrating data from advertising platforms, analytics tools, CRM systems, and other marketing technologies.
• Advanced SQL skills required.
• Experience with Python for analytics is highly desirable.
• Experience with Looker, LookML, or similar BI platforms strongly preferred.
• Ability to communicate analytical concepts to executive stakeholders.
• Experience working across multiple brands, business units, or product lines preferred.

Preferred

• Experience with Python for analytics is highly desirable.
• Experience with Looker, LookML, or similar BI platforms strongly preferred.
• Insurance, financial services, fintech, or other highly regulated industries are advantageous.
• Experience working across multiple brands, business units, or product lines preferred.