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. We envision a world where crypto reshapes the global financial system, internet, and money to create greater choice, independence, and opportunity for all — bridging traditional finance with the emerging cryptoeconomy in a way that is more open, fair, and secure. As a publicly traded company, Gemini is poised to accelerate this vision with greater scale, reach, and impact.
About the Department
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. From building scalable pipelines and platforms, to enabling cutting-edge machine learning, to ensuring governance and cost efficiency, we deliver the foundation for smarter decisions and breakthrough products. We thrive at the intersection of crypto, technology, and finance, and we’re united by a shared mission: to unlock the full potential of Gemini’s data to drive growth, efficiency, and customer impact.
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
Requirements
- 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 and automation is preferred
- Experience translating business requirements into scalable dimensional data models and actionable insights
- Experience with modern data transformation frameworks such as dbt
- Experienced in working collaboratively across different teams and departments
- Strong technical and business communication
Preferred Qualifications
- Experience designing enterprise-scale dimensional data models and semantic layers
- Experience building trusted, reusable datasets for self-service analytics
- Knowledge and experience of blockchain, financial markets, banking or exchanges
Benefits
- Competitive starting pay
- A discretionary annual bonus
- Long-term incentive in the form of a new hire equity grant
- Comprehensive health plans
- 401K with company matching
- Paid Parental Leave
- Flexible time off
Pay
The base salary range for this role is between $126,000 - $180,000 in the State of New York. This range is not inclusive of our discretionary bonus or equity package. When determining a candidate’s compensation, we consider a number of factors including skillset, experience, job scope, and current market data.
Schedule
In the United States, we offer a hybrid work approach at our hub offices, balancing the benefits of in-person collaboration with the flexibility of remote work. Expectations may vary by location and role. Employees who do not live near one of our hubs are part of our remote workforce. All employees, however, are required to onboard in-person at one of our office locations.