Senior Analytics Engineer

About the Company

Gemini is a global crypto and Web3 platform founded by Cameron and Tyler Winklevoss in 2014, offering a wide range of simple, reliable, and secure crypto products and services to individuals and institutions in over 70 countries. Our mission is to unlock the next era of financial, creative, and personal freedom by providing trusted access to the decentralized future.

The Department: Data

At Gemini, our Data team is the engine that powers insight, innovation, and trust across the company. We bring together world-class data engineers, platform engineers, machine learning engineers, analytics engineers, and data scientists — all working in harmony to transform raw information into secure, reliable, and actionable intelligence.

The Role: Senior Analytics Engineer

As a member of our data team, you'll deliver high-quality work while designing scalable data models and solving challenges that impact the team's data architecture. You'll stay current with advances in the modern data ecosystem and apply them to build scalable solutions that align with the team's long-term goals. Your work will involve identifying root causes, documenting solutions, and implementing them with operational excellence in mind through data quality, validation, automation, and maintainability. Communicating technical concepts and analytical insights with leaders across the organization is paramount to success.

Responsibilities

• Design, architect and implement best-in-class data warehousing and reporting solutions
• Design, build, and evolve scalable dimensional data models that serve as trusted foundations for Data Warehouse and BI solutions
• Partner with product managers, data engineers, and business stakeholders to translate business requirements into scalable data models and actionable insights
• Perform analysis to derive actionable insights for key stakeholders
• Perform root cause analysis and resolve production and data issues
• Develop and maintain automated data quality checks, validation frameworks, and testing to ensure the accuracy and reliability of data assets
• Optimize SQL transformations and data models for performance, scalability, and maintainability
• Build and maintain data dictionary and process documentation
• Research new tools and technologies to improve existing processes

Minimum Qualifications

• 5+ years of experience in analytics engineering, data engineering, or similar roles
• Strong experience designing dimensional data models and schemas for enterprise data warehouses
• Strong experience designing, building, and maintaining scalable data transformation pipelines
• Strong experience developing analytics and BI solutions using platforms such as Looker, Tableau, or Power BI
• Advanced SQL skills are required. Proficiency with Python for data transformation