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This position is needed to serve as architect of the marketing organization’s automated intelligence engine, unifying disparate data ecosystems into a cohesive, high-velocity growth platform. You will ensure the integrity of our underlying data architecture, implementing sophisticated automation that transforms reporting and analytics velocity, and establish a "best-in-class" work ecosystem through advanced generative AI systems. As the internal automation champion, you will drive the strategic scaling of the entire marketing analytics organization, institutionalizing efficiency and dramatically accelerating the 'velocity to value' for global stakeholders.
Job Responsibility:
Architect automated frameworks for reporting & analytics to drive weekly executive cadences, replacing manual effort with high-velocity, real-time insights
Consult with cross-functional team members to identify workflow bottlenecks and architect automated systems that maximize departmental throughput
Conduct comprehensive audits of analytics and reporting workflows to design and implement optimized, automated processes that eliminate structural inefficiencies and maximize team output
Drive enhanced capability and automation for third-party data enrichment tools
Design and govern a shared AI foundation within the marketing strategy & analytics team, including a centralized repository of optimized skills, prompts, "gems," and automated scripts
Act as the lead architect for AI-driven workflows - leveraging OpenAI, Claude, and Gemini - to automate Query optimization, Insights generation while actively training the broader team to institutionalize these efficiencies
Serve as the primary technical lead for collaboration with our Enterprise Tech (ET) teams, overseeing Segment integrations, BigQuery architecture, and overarching data governance to ensure a secure, scalable environment
Establish the automated data frameworks necessary to unify disparate top-of-funnel and bottom-of-funnel signals, providing a comprehensive, end-to-end view of marketing’s impact on pipeline and LTV
Requirements:
5+ years of experience in analytics engineering or data operations, with a focus on building automated, high-velocity reporting frameworks and intelligence systems
Demonstrated experience applying Generative AI and LLM-driven solutions (OpenAI, Claude, Gemini) to automate complex analytics workflows and data synthesis at scale
Expert-level SQL proficiency (Presto/BigQuery, CTEs, window functions) and the ability to leverage Python for data automation and systems integration
Advanced experience in prompt engineering for complex data extraction, automated code generation, and sophisticated narrative analysis
Deep understanding of the data lifecycle, including ETL/ELT processes, data warehousing, and the integration of third-party enrichment tools into a centralized ecosystem
A passion for "socializing" technical advancements and a proven ability to lead team-wide training to institutionalize new tools and workflows
Proven track record of partnering with Data Engineering and Enterprise Tech teams to govern data architecture while successfully gathering requirements from non-technical stakeholders
Nice to have:
Familiarity with Salesforce object structures (Leads, Contacts, Opportunities) and the logic required for complex pipeline and revenue attribution
Hands-on experience with the "technical plumbing" of web analytics, including GA4, Google Tag Manager (GTM), and Adobe Target, specifically regarding how they feed into downstream data warehouses
Advanced proficiency in Looker or Tableau, with a focus on building scalable, automated dashboards that empower stakeholders with self-service insights
Experience managing the data flow between CDPs (e.g., Segment), marketing automation platforms, and Business Intelligence layers to ensure a "single source of truth"
Track record of translating vague business questions into technical data requirements and automated solutions