Senior Data Analyst

February 28

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Rebrandly

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Rebrandly is a leading link management platform that empowers users to transform every link into a powerful, branded connection. As the #1 platform for branded short links, Rebrandly offers essential tools to scale brands, businesses, data, and systems through reliable link management solutions. The company provides in-depth click data analysis to enhance link performance and elevate user experience. Committed to security and compliance, Rebrandly is SOC 2 Type II certified, and GDPR, HIPAA, and CCPA compliant. Millions of users trust Rebrandly's infrastructure for enhancing their digital presence and conversions.

Branded links • Online Branding • Brand • URL Shortener • Link Management

51 - 200 employees

Founded 2015

🤝 B2B

☁️ SaaS

🔌 API

📋 Description

• As Rebrandly’s Data Analyst, you will shape our data strategy and build the business intelligence infrastructure that drives our company’s decision-making. • You will transform complex data into actionable insights that directly influence strategy and operations across all departments, with high visibility and impact. • You are a self-motivated problem solver who is passionate about analysing large datasets and transforming data into insights. • You thrive in a collaborative environment where your technical expertise contributes to a shared mission. • You’re excited to work on impactful projects and have experience using modern data infrastructure to build reliable, scalable, and efficient data solutions.

🎯 Requirements

• Proven track record of a minimum of 5 years in a highly analytical role. • Strong analytical skills and solid understanding of statistical methods, with the ability to extract meaningful insights from large and complex data sets. • Solid experience with SQL and data visualization/analytics tools (e.g., Tableau, Mixpanel, Metabase). • 5+ years of experience in a programming language (e.g., Python). • Experience designing data solutions, modeling data, and developing ETL/ELT pipelines at large scale. • Experience developing large-scale data solutions using cloud platforms (e.g., AWS, Azure, Google Cloud). • Experience in data cataloging, classification, data quality, metadata management, and data lifecycle. • Understand the importance of engineering with security’s best practices in mind. • Experience working with product analytics tools and tracking user behavior. • Experience with growth experimentation and A/B testing frameworks. • You understand SaaS metrics. • You are empathetic and eager to see the world from the user's perspective. • You’re energized by business impact & a self-starter: you love to drive the direction of ambiguous projects. • Drive to take ownership of and debug complex data transformation pipelines and data models.