Senior Data Analyst, Rebrandly

• 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
• You have experience analysing large datasets, building data systems, and working independently
• 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
• If you're a curious and passionate person, we want to hear from you

Desirable

• 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
• Analyze and Visualize Data: Identify trends and patterns, create compelling visualizations, and prepare reports that make complex data understandable
• Collaborate Cross-Functionally: Work with product teams, engineers, and management to understand requirements and deliver solutions
• Build and Maintain Infrastructure: Ingest and egress frameworks for data pipelines that stitch together various data sources
• Optimize data pipelines to support business analytics, machine learning models, and product features
• Ensure Data Quality: Implement governance protocols to maintain data integrity throughout our system infrastructure
• Lead Data Strategy by owning the roadmap for our company’s data platform and establishing best practices
• Support User Tracking by implementing and maintaining effective event tracking
• Standardize engineering best practices and implementation methodologies