Digital Marketing Data Analyst: Insights & Experimentation

SteelSeries; United States; Hybrid; USD 90,000 - 120,000; Full time

Job summary

GN is seeking a Digital Marketing Data Analyst for North America to join the Global Marketing — Digital Media team. You will serve as the data and measurement backbone of our digital media practice, owning reporting infrastructure, designing experiments, and leading advanced measurement initiatives.

You will build performance reports across channels using Power BI, define KPI frameworks, analyze A/B tests, and collaborate with engineering on data pipelines.

Qualifications

• Strong background in digital or media analytics.
• Proficient in SQL and data warehouses.
• Experience building dashboards in BI tools.
• Understanding paid media platforms and their data outputs.
• Comfortable designing and analyzing experiments.
• Excellent communication of insights to technical and non-technical audiences.
• Experience with data clean rooms or attribution models is a plus.

Responsibilities

• Build and improve performance reporting across channels, including Power BI dashboards.
• Define KPI frameworks and identify trends, anomalies, and optimization opportunities.
• Design and analyze A/B tests and deliver 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

Digital analytics

SQL

Experiment design

Communication

Tools

Power BI

Data warehouses

Python

R

Job description

GN is seeking a Digital Marketing Data Analyst for North America to join the Global Marketing — Digital Media team. You will serve as the data and measurement backbone of our digital media practice, owning reporting infrastructure, designing experiments, and leading advanced measurement initiatives.

You will build performance reports across channels using Power BI, define KPI frameworks, analyze A/B tests, and collaborate with engineering on data pipelines.