Marketing Data Analyst

What you’ll do

• Build and maintain automated ELT pipelines that pull data from HubSpot, GA4, social, video, podcast, paid media, and event platforms into BigQuery using APIs and native integrations.
• Organize marketing and audience data in BigQuery using a medallion architecture, and use Dataform transformations to convert raw and semi-structured sources (including GA4 event export and JSON API responses) into cleaned, reporting-ready tables.
• Document data models, shared identifiers, transformation rules, and metric definitions in a data dictionary so marketing, audience, CRM, web, and content data connect reliably.
• Monitor pipeline health and data freshness so issues are caught early, and manage work with Git and GitHub for reproducibility and maintainability.
• Ensure responsible handling of audience and contact data, credentials, and system access in line with Stanford privacy and information security policies and applicable regulations.
• Support accurate campaign performance measurement by ensuring campaigns launch with the right tracking, tagging, and measurement plans, including consistent campaign naming and UTM conventions.
• Partner with web developers to define GA4 event and data layer specifications, and QA tracking using tools such as Google Tag Manager preview mode and GA4 DebugView.
• Troubleshoot tracking and data-quality issues across Hoover’s web team and external partners, including investigating discrepancies between GA4, HubSpot, and platform-reported figures.
• Analyze who Hoover is reaching and how effectively priority audiences are engaged, using CRM, web, platform, event, and survey data.
• Develop measurement frameworks and KPIs for reach, resonance, and relationships, distinguishing high-volume activity from engaged reading, viewing, and listening.
• Build audience cohorts and segments based on acquisition source, content interests, behavior, and relationship to Hoover.
• Run pre-, during-, and post-campaign analyses against objectives, and identify what audience, creative, message, format, timing, and platform elements drive performance.
• Measure incremental impact of paid promotion using holdout groups, geographic tests, or platform lift studies where feasible; separate paid, organic, earned, and direct activity.
• Assess marketing costs and outcomes, including cost per engaged visitor, new subscriber, and event registrant, to support evidence-based budget allocation.
• Design and analyze A/B and multivariate tests across email, web, landing pages, paid media, messaging, and creative, with hypotheses, success metrics, minimum detectable effects, and required sample sizes.
• Create automated cross-channel dashboards (for example, in Looker Studio built on BigQuery reporting tables) and produce regular reporting and executive-level analyses for nontechnical audiences.
• Proactively identify patterns, opportunities, and risks in the data, then follow through to evaluate whether recommendations improved outcomes.
• Contribute additional duties as needed.

What you bring

• Bachelor’s degree in a relevant field and two years of relevant experience, or a combination of education and relevant experience solving analytical problems using quantitative approaches.
• Experience in marketing analytics, audience analytics, or digital analytics, working directly with marketing, communications, or content teams.
• Demonstrated ability to combine data from multiple platforms and turn it into recommendations that shaped marketing, content, or audience decisions.
• Ability to communicate analytical findings to nontechnical stakeholders.

Technical skills and tools

• GA4 (event-based data model, custom events/parameters/custom dimensions, key events, Explorations) and correct interpretation of reporting impacts from attribution settings, consent mode, and data thresholding.
• Data layer and Google Tag Manager, including tracking specifications and debugging with preview tools.
• HubSpot experience with contacts, custom objects, properties, lifecycle stages, lists, marketing email, forms, and subscriptions, plus awareness of email open-rate limitations (including Apple Mail Privacy Protection).
• UTM tracking, campaign taxonomy, Google Search Console, and native analytics for platforms such as YouTube Studio, Meta Business Suite, LinkedIn, and Google Ads.
• BigQuery and Dataform for storing, querying, and transforming data (including nested/repeated fields), with cost-aware querying.
• SQL for joins, window functions, CTEs, and working with JSON/text via regex and text functions.
• Python and JavaScript for data processing, automation, and integration (including API calls, cleaning, statistical analysis, and GTM-related scripting).
• REST API integration and ELT pipelines on Google Cloud, including authentication, pagination, rate limits, and monitoring/error handling.
• Medallion architecture and mapping reporting logic to documented metric definitions using shared identifiers across systems (CRM record IDs, GA4 user IDs, UTM parameters).
• Git/GitHub, Visual Studio Code, and command-line tools such as Bash, gcloud, and bq.
• Experimentation and statistical testing experience, including A/B and multivariate testing with power analysis, confidence intervals, and correct use of two-proportion z-tests, t-tests, and chi-square tests.
• Dashboarding in Looker Studio and/or Tableau or Power BI.
• Google Sheets and Excel for quick-turn, stakeholder-ready work.

Preferred experience

• Experience with cohort analysis, audience segmentation, funnel analysis, and audience journey analysis.
• Experience with attribution modeling, incrementality testing, or marketing mix modeling (for example, Google’s Meridian or Meta’s Robyn).
• Experience with regression analysis, Bayesian or sequential testing methods, and causal inference techniques such as difference-in-differences or synthetic control.
• Experience with dbt, managed ELT connectors (such as Fivetran, Supermetrics, or Airbyte), Google Cloud services like Cloud Run/Cloud Scheduler/Secret Manager, and CI/CD tools such as GitHub Actions.
• Experience using AI responsibly in line with institutional policy, including BigQuery ML or NLP workflows, and AI coding assistants to accelerate development.
• Familiarity with web and UX analytics (such as Microsoft Clarity, Hotjar, Chartbeat, Parse.ly), SEO tools (Semrush, Ahrefs), survey tools (Qualtrics, SurveyMonkey), and social listening (Sprout Social, Brandwatch).
• Experience in media, publishing, think tanks, nonprofits, higher education, or other mission-driven, content-focused organizations.
• Interest in public policy, economics, history, or current affairs, and how ideas reach and influence audiences.