Responsibilities

• Lead client-facing analytics engagements, translating data into insight that is relevant to the client's industry, business model, and marketing objectives
• Guide clients through measurement framework development, helping them identify the KPIs that matter for their vertical and connect those metrics to marketing performance
• Facilitate workshops focused on analytics maturity, MarTech evaluation, and gap analysis for new technology investment
• Present findings and recommendations to both marketing practitioners and senior stakeholders, adjusting depth and framing for the audience
• Partner with the Director of Solutions Engineering to define data requirements, event taxonomy, and structural standards that support downstream reporting and visualization
• Communicate clearly with solutions engineers about what data needs to be captured, how it should be structured, and what the downstream reporting use case requires
• Review and contribute to solutions architecture conversations with enough technical fluency to ask the right questions and surface the right tradeoffs
• Create wireframes and design concepts for marketing dashboards and data visualization
• Go hands-on in platform to build or configure reporting environments that deliver the right level of insight for the audience
• Translate complex datasets into clear, decision-ready narratives for marketing stakeholders

Requirements

• Vertical fluency across multiple marketing contexts. You can walk into an ecommerce engagement and speak to ROAS, AOV, and cart abandonment, and walk into a lead generation engagement and speak to pipeline, sales velocity, and marketing-influenced revenue
• Strong command of marketing KPIs across paid media, owned channels, CRM, and customer lifecycle
• Experience contributing to MarTech assessments, RFI processes, or technology roadmap engagements
• The ability to hold a technical conversation with a solutions engineer and a strategic conversation with a CMO, sometimes on the same day
• Comfort operating in ambiguous, client-facing environments where the problem is rarely fully defined at the start.
• Familiarity with the cloud ecosystems, like GCP, as it applies to marketing data infrastructure including querying and data modeling, reporting and visualization, and enough working knowledge of serverless functions to understand how data moves through an event-driven pipeline and where reporting requirements need to be introduced upstream.
• Working coding knowledge with languages like Python or JavaScript. You are not expected to write production ready code daily, but you can write or adapt scripts when the situation calls for it, read and pressure test solutions, and understand the logic behind data transformations well enough to ask the right questions.
• Comfort reviewing technical documentation, data dictionaries, and event taxonomies to identify gaps and surface the right tradeoffs in an architecture conversation.
• Enough fluency with data pipeline architecture, event tracking schemas, and transformation logic to guide visualization work from requirements through to delivery. Ability to think through what the data needs to look like before it gets to the dashboard and communicate that clearly to the team building it.

The Imaginarium

• The Imaginarium is a full-service strategy, customer experience, creative, and digital marketing agency driven by hospitality, excellence, and accountability. Our team builds and executes modern marketing systems that align strategy and execution, so you can move fast and grow with confidence.