Requirements

Expected technologies

Google Analytics

Google Tag Manager

A/B Testing Tools

BiqQuery

SQL

Hotjar

Clarity Design System

Microsoft Power BI

Operating system

Windows

Our requirements

• 7+ years of experience as an eCommerce Data Analyst or in a similar analytics-focused role.
• Proven expertise with GA (including GA4), GTM, A/B testing tools, and web analytics.
• Advanced knowledge of SQL, BigQuery, and Excel.
• Hands-on experience with Power BI, Clarity, or comparable tools.
• Strong understanding of eCommerce platform architecture, product data flows, and transaction processes.
• Degree in Digital Marketing, Mathematics, Computer Science, or related discipline.
• Excellent analytical, problem-solving, and project management skills.
• Business acumen and strategic understanding.
• Curiosity and inquisitiveness are a must.
• Experience working in Agile/Scrum environments.
• Exceptional communication and stakeholder management skills.
• Fluent English, both written and spoken.

Your responsibilities

• Provide advanced expertise and vision on Webanalytics concepts for the organization.
• Lead and oversee the setup, configuration, and optimization of Google Analytics (GA4) tracking, utilizing Google Tag Manager (GTM).
• Mentor junior team members, fostering growth and expertise within the analytics team.
• Design and document measurement plans, implement and test GA tracking.
• Act as a key liaison between digital product, marketing, developers, and data engineering teams to ensure tracking aligns with business goals.
• Conduct end-to-end analysis – from gathering requirements, exploring data, building dashboards (Power BI), to delivering recommendations.
• Analyze customer behavior, transactional trends, and website performance to identify opportunities for revenue and conversion growth.
• Provide training and support for GA users and promote best practices in web analytics and stay updated on industry trends and emerging technologies.
• Develop and refine data transformations in BigQuery for eCommerce data model.
• Support and enhance A/B testing frameworks and experimentation processes.