Requisition ID:
66588
Title:
Marketing Data Analyst II
At Arthrex, we are dedicated to helping surgeons treat their patients better through innovative orthopedic medical devices, surgical technologies, and medical education. Headquartered in beautiful Naples, Florida, Arthrex is a global leader in orthopedics and a company driven by innovation, excellence, and a passion for improving patient outcomes.
We are seeking a highly analytical, detail-oriented Marketing Data Analyst to join our dynamic Marketing team. This role is ideal for someone who thrives on transforming data into actionable insights, enjoys solving complex business challenges, and wants to make a meaningful impact in a fast-paced, collaborative environment. If you’re passionate about data, storytelling through analytics, and helping drive strategic marketing decisions for a world-class organization, we’d love to hear from you.
Join a company known for its exceptional culture, industry-leading innovation, and commitment to employee growth and development.
Main Objective:
The Marketing Data Analyst works with Marketing Operations, Data & Analytics Center of Excellence, Product Management, and other stakeholders to provide comprehensive data analysis, unlock opportunities through valuable insights and drive decision support solutions leveraging the best-in-class data & analytics tools. The analyst will help mature the use of data with user-friendly analytical tools, dashboards, and advanced analytics so that relevant information can be efficiently gathered, shared, and interpreted by our business teams and their partners.
Essential Duties and Responsibilities:
• Implement and manage Google Analytics to track website traffic, user behavior, and conversion rates.
• Utilize Google Analytics to monitor and analyze the performance of digital marketing campaigns, identifying areas for improvement.
• Extract data from Google Analytics to provide insights on website user journeys and identify conversion funnel bottlenecks.
• Extract and transform data from various sources and load it into BigQuery for in-depth analysis.
• Write SQL queries and utilize BigQuery's data processing capabilities to analyze large datasets effectively.
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