BI Analyst (High-Value Enterprise Accounts)

We are seeking a highly technical, data-driven BI 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