Digital Marketing Data Analyst — Build Dashboards & Insights

GN Group; United States; Hybrid; USD 90,000 - 125,000; Full time

Job summary

GN Group in North America is seeking a Digital Marketing Data Analyst to serve as the data and measurement backbone of our digital media practice. You will own reporting infrastructure, design experiments, and lead advanced measurement initiatives like data clean rooms.

The role emphasizes SQL, building dashboards in Power BI, collaboration with engineering on data pipelines, and translating insights for stakeholders and leadership.

Qualifications

• Strong background in digital or media analytics.
• Proficient in SQL and working with data warehouses.
• Experience building dashboards in BI tools.
• Understand paid media platforms and their data outputs.
• Comfortable designing and analyzing experiments.
• Able to communicate insights clearly to technical and non-technical audiences.
• Experience with data clean rooms, attribution models, or Python/R is beneficial.

Responsibilities

• Build and improve performance reporting across channels, including Power BI dashboards that drive decisions.
• Define KPI frameworks and identify trends, anomalies, and optimization opportunities.
• Design and analyze A/B tests and deliver clear, actionable recommendations.
• Support data clean room initiatives and incrementality measurement.
• Write SQL queries to develop unified cross-platform performance insights.
• Collaborate with engineering on data pipelines and tracking frameworks.
• Translate analysis into clear insights for stakeholders and leadership.

Skills

SQL

Power BI

Data analytics

Experiment design

Data pipelines

Communication of insights

Python

R

Tools

Python

R

Job description

GN Group in North America is seeking a Digital Marketing Data Analyst to serve as the data and measurement backbone of our digital media practice. You will own reporting infrastructure, design experiments, and lead advanced measurement initiatives like data clean rooms.

The role emphasizes SQL, building dashboards in Power BI, collaboration with engineering on data pipelines, and translating insights for stakeholders and leadership.