We are seeking a highly technical, data-driven Insights & Measurement Analyst to support a small number of high-value enterprise accounts. This role is built for someone who lives in large, complex datasets and turns them into clear, decision-grade insights. Working alongside an Account, Strategy and Media Directors, you will own the analytical layer for each assigned client - generating performance insights, producing forecasts, and surfacing the patterns that drive business outcomes. You will operate fluently inside client-owned data warehouses such as BigQuery, Snowflake, and Sigma, build BI environments in tools like Power BI/Tableau, and translate ambiguous business questions into structured analytical work. This role centers on developing a deep quantitative understanding of each client's business and using that fluency to inform strategy, investment, and forecasting decisions. The position plays a critical cross-functional role between Strategy, Paid Media, Client Services, and Analytics. What You'll Do Data Analysis & Insight Generation • Synthesize large, multi-source datasets across paid media, web, CRM, ecommerce, offline conversions, and call tracking into clear performance narratives • Conduct deep-dive analyses on channel contribution, funnel efficiency, audience segmentation, LTV, CAC, MER, and cohort behavior • Surface hidden patterns, anomalies, and opportunities by applying statistical methods to complex, multi-dimensional datasets • Translate raw data into business-aligned insights tied to revenue, pipeline, retention, and growth outcomes • Partner with Strategy leadership to inform testing roadmaps, investment decisions, and budget reallocation Forecasting & Predictive Modeling • Build and maintain forecasting models for revenue, spend, CAC, ROAS, CPA, and other KPIs across paid channels, ecommerce, and lead-gen environments • Develop scenario models (baseline vs. optimized) that project incremental opportunity from strategic shifts • Apply seasonality decomposition, time-series methods, and regression-based projection techniques • Quantify the financial impact of audit findings, optimization recommendations, and budget changes • Surface leading indicators of underperformance before they appear in lagging metrics Business Intelligence & Data Visualization • Build and maintain BI environments using tools such as Power BI, Looker, Tableau, and Sigma • Design semantic data models, DAX measures, and reusable datasets that scale across clients and account types • Build executive-ready dashboards that translate complex datasets into clear, narrative-driven views of performance • Establish single-source-of-truth reporting frameworks that reconcile platform data with CRM and ecommerce truth • Optimize query performance, data refresh patterns, and cost efficiency across BI infrastructure Working Within Client Data Environments • Operate fluently inside client-owned data warehouses, including BigQuery, Snowflake, and Sigma, to query, model, and analyze marketing and business data • Write performant SQL against client schemas to build the datasets, views, and aggregations that power analysis and reporting • Develop attribution logic in the warehouse layer (multi-touch, last-click, position-based, custom blends) using whatever stack the client provides • Adapt to varying data architectures, naming conventions, and governance models across enterprise client environments • Partner with client data teams to align on definitions, source-of-truth logic, and access patterns • Support offline conversion pipelines via platform APIs (Google Ads, Meta CAPI) where data engineering input is required Measurement Foundation & Data Integrity • Validate that conversion tracking, attribution logic, and data flow across Google Ads, Meta, LinkedIn, TikTok, GA4, and CRM environments feed the warehouse cleanly and consistently • Partner with tag management specialists to translate analytical requirements into data layer specifications • Identify discrepancies between platform reporting and source-of-truth, and trace them to root cause • Enforce consistent event taxonomies, UTM structures, and naming conventions at the data layer • Ensure analytical outputs respect privacy frameworks and consent management requirements Cross-Functional Partnership • Act as the analytical counterpart to the Strategy Director or Enterprise Account Director on assigned enterprise accounts • Serve as the agency's go-to voice for diagnosing performance issues, sizing opportunities, and pressure-testing strategic hypotheses with data • Translate technical findings into language that resonates with C-level client stakeholders • Collaborate with Paid Media, SEO, Client Services, and Strategy teams to align analytical outputs with execution What You'll Bring • 6+ years of experience in digital analytics, business intelligence, marketing data science, or a closely related discipline • Expert-level SQL with hands-on experience working inside client-owned warehouses such as BigQuery, Snowflake, and Sigma: CTEs, window functions, materialized views, and cost-aware query design • Advanced BI proficiency: data modeling, DAX, Power Query, performance optimization, and row-level security • Strong adoption and comfort with AI tools including Claude Code, Cursor or Codex. • Proven experience working within client data environments to unify paid media, web, CRM, and revenue data into analysis-ready datasets • Strong working knowledge of GA4, Google Ads, Meta Ads, and the underlying data structures of each platform's exports and APIs • Demonstrated experience building forecasting models using time-series methods, regression, or scenario-based modeling • Hands-on Python (preferred) or R for statistical analysis, pandas-based data manipulation, and reproducible analytical workflows • Strong understanding of multi-touch attribution, marketing mix concepts, and cross-channel measurement principles • Experience with offline conversion tracking