Marketing Analytics Specialist

Keenfinity•Burnsville, MN

8h•$72,000 - $95,000

About The Position

The Data Analyst will be the measurement engine behind our digital experience stack—making sure we can see what’s happening, understand why and act on it. This role will own the implementation and maintenance of GA4, GTM, and data layer tracking across our key platforms, build dashboards for marketing and digital teams, and help teams run experiments and interpret results. This role will blend hands-on analytics engineering (tags, events, data layers) with storytelling: turning complex data into insights, narratives, and recommendations that influence roadmaps and campaign decisions.

Requirements

Bachelor’s degree in business, marketing, statistics, data science, economics, information systems, or a related field.
3–5 years of experience in digital/web or marketing analytics, with hands-on ownership of GA4 and Google Tag Manager (events, conversions, custom dimensions/metrics, and data layer–based tagging).
Ability to remain in a stationary position (sitting or standing) for extended periods while working at a computer, with regular opportunities to move or change position.
Requires visual acuity to view a computer monitor and read documents, as well as the ability to communicate clearly in person and through digital platforms.
Ability to maintain focus and productivity in a typical office environment with standard noise levels and ergonomic equipment.
Ability to occasionally lift and move standard office items or equipment (such as laptops, marketing materials, or small demo units) up to 25–30 pounds, with or without reasonable accommodation.

Nice To Haves

Proven experience building and maintaining self-serve dashboards in tools such as Power BI, Tableau, or Looker, including standardizing core metrics and visualizing performance for non-technical stakeholders.
Working knowledge of SQL (and/or a scripting language such as Python, Json or R) and experience partnering with BI/data engineering teams and data warehouses (e.g., BigQuery, Snowflake, Azure) to support reporting and analysis.
Experience supporting A/B testing and experimentation (hypothesis design, success metrics, and result interpretation), along with familiarity with SEO, GEO, and web performance concepts and tools (e.g., Search Console, Core Web Vitals, PageSpeed/Lighthouse).
Exposure to AI Automation, API Integration, and ML-powered digital experiences (such as recommendations, personalization, or semantic search) and the ability to measure their performance and turn findings into clear, actionable insights and recommendations.

Responsibilities

Own the configuration, implementation, and maintenance of GA4 and Google Tag Manager across web and digital properties.
Design and manage event tracking, custom dimensions, conversions, and enhanced measurement for key user journeys.
Collaborate with developers, digital platform owners, and BI to ensure a clean, well-documented data layer that supports reliable reporting.
Regularly audit tracking to identify gaps, duplicates, or inaccurate tags and implement fixes.
Build and maintain self-serve dashboards in tools like Power BI, Tableau, or Looker for marketing, digital, and leadership teams.
Standardize core metrics and definitions (traffic, engagement, lead quality, funnel performance, content performance, etc.).
Deliver regular performance reports (weekly/monthly/quarterly) highlighting trends, issues, and opportunities—not just numbers.
Support and help run A/B tests and experiments across the website and other digital surfaces.
Partner with digital, UX, and content teams to define hypotheses, success metrics, and test design.
Conduct basic causal impact analysis and lift measurement, and clearly communicate what worked, what didn’t, and what to do next.
Analyze Core Web Vitals, page performance, and behavioral patterns (bounce rates, scroll depth, funnel drop-offs).
Track and report on SEO performance (organic traffic, keywords, landing pages) in partnership with SEO specialists or agencies.
Monitor on-site search behavior and navigation patterns to identify content gaps, UX friction, and new content opportunities.
Translate numbers into clear, actionable insights for marketing, content, and digital platform teams.
Provide input into platform and campaign roadmaps based on what the data actually shows—e.g., where to invest, what to fix, what to expand.
Support business cases for new features or experiments with data-backed recommendations and projections.
Collaborate closely with BI / data engineering on data ingestion, modeling, and integration into the broader data warehouse or lake.
Participate in data layer QA, ensuring event and user data are accurate, consistent, and usable downstream.
Help align digital analytics with broader business KPIs (pipeline, revenue, customer retention) and multi-touch attribution efforts where appropriate.
Partner with digital experience, product, and engineering teams to define measurement requirements and success metrics for AI-powered features such as recommendations, predictive scoring, semantic search, and personalization.
Work with BI and data engineering to ensure the right events, features, and datasets are exposed via APIs and data pipelines to support AI and ML use cases across web and other digital properties.
Monitor the performance, quality, and fairness of AI-driven experiences, surfacing insights, anomalies, and improvement opportunities to stakeholders.
Document AI-related metrics, data flows, and dependencies so they are understandable, auditable, and maintainable across teams.