Job Opportunities API

Key Responsibilities: •      Own executive-level analytical requests end to end: scope ambiguous business questions with senior stakeholders, define the methodology, assumptions, and source of truth, and deliver validated, approval-ready findings within priorities set by the VP of Business Intelligence and the CMO. •      Design and govern the marketing data model and semantic layer, including club and channel dimension tables, KPI definitions, channel mappings, and calculation standards used across marketing reporting. Serve as the subject matter export on reporting classifications. •      Own the analysis quality framework for marketing analytics: set the validation and reconciliation standards used across the BI team, provide technical review of marketing-related work produced by consultants and cross-functional partners, and certify the accuracy of externally distributed deliverables. •      Design campaign measurement methodology, incrementality and holdout test design, and year over year comparability standards, and defend the methodology to executive audiences. •      Develop and maintain executive-grade Power BI dashboards and semantic models covering lead generation, conversion, retention, campaign performance, and ROI. •      Design and execute advanced analytics initiatives, including audience segmentation and clustering, survey research analysis, propensity modeling, and forecasting of spend versus performance. •      Translate findings into concise recommendations and present directly to the CMO, ownership, and senior operators; anticipate follow-up questions and defend every number, assumption, and conclusion presented. •      Serve as the analytical partner to the CMO organization on emerging initiatives: member research and clustering-based segmentation, referral program measurement, lifecycle and re-engagement campaigns, digital funnel analysis, and defining marketing technology data collection requirements with IT (for example, referral attribution, SMS engagement, and abandoned cart data). •      Support the migration of marketing analytics to the Databricks lakehouse platform and re-platform existing marketing reporting as the company transitions its analytics infrastructure. •      Maintain rigorous data governance, accuracy, documentation, and reproducibility in all analyses, dashboards, and data assets. Required Knowledge, Skills & Abilities: Technical Skills •      Expert-level SQL for complex querying, data modeling, and validation across warehouse sources. •      Expert-level Power BI across the full stack, not DAX alone: dimensional (star schema) design, building semantic models, relationship and storage mode decisions, incremental refresh, row-level security, deployment pipelines, and performance tuning. Candidates must be able to design and build the data model themselves; this role does not have a data science or data engineering team. •      Expert DAX, including filter context, context transition, and measure design that behaves correctly across report pages and visuals. •      Working statistical foundation: experiment and test design, significance testing, segmentation and clustering techniques, and regression-based analysis. •      Python or R for advanced analysis, automation, or modeling; PySpark a plus. •      Experience with Databricks or a comparable Spark-based lakehouse platform strongly preferred. The company will be migrating its analytics infrastructure to Databricks and this role will be integral in the marketing analytics transition. •      Hands-on experience with Google Analytics (GA4) and HubSpot, including connecting their data to warehouse reporting and understanding their attribution models and limitations; both are used heavily in this role. Experience with CRM systems, paid media platforms, and marketing automation more broadly.