Develop infrastructure to deliver actionable insights: Solution across multiple tool sets. including Adobe Analytics, GA4, Salesforce, and BigQuery. Leverage multipoint architecture to deliver robust dashboards to drive customer journey insights and segment creation for personalization activities.
Stitch & synthesize data: Query, extract, and blend large datasets from multiple sources including our web analytics platform, BI database, CRM, and marketing automation platforms.
Champion data-driven culture: Advocate for data literacy within the marketing organization, proactively sharing insights in internal communication forums and helping stakeholders ask the right questions.
Govern tag management: Implement tracking across our TMS platforms: Zaraz, GTM, Adobe Launch
Pixel governance and management: Deliver requirements to marketing engineering teams for pixel deployment. Audit properties for pixel counts and relevance.
Requirements
6+ years experience working in a large B2B, D2C, SaaS, or enterprise cloud company
5+ years of experience in a data analytics role, preferably within marketing, web analytics, or product analytics
5+ years experience implementing data analytics tracking systems.
Deep, hands-on experience with at least one enterprise-level web analytics platform (e.g., Adobe Analytics, Google Analytics 4, etc.) in a very high web traffic environment
Experience with A/B/n testing implementations
Experience with data warehouses like BigQuery, Snowflake or similar
Proficiency in SQL for querying complex, large-scale datasets
Knowledge of statistical programming languages, such as Python or R is a plus
Familiarity with analyzing data from CRM (e.g., Salesforce) and Marketing Automation (e.g., Marketo) platforms to create a full-funnel view
Proven expertise in creating impactful dashboards and data visualizations using tools like Tableau, Looker Studio, etc
Exceptional communication and storytelling skills, with the ability to translate analytical findings into clear, concise, and actionable recommendations
Bachelor's degree in a quantitative field (e.g., Statistics, Economics, Computer Science, Mathematics) or equivalent practical experience is preferred.
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