Head of Data

About the Company

Gemini is a global crypto and Web3 platform founded by Tyler Winklevoss and Cameron Winklevoss in 2014. Gemini offers a wide range of crypto products and services for individuals and institutions in over 70 countries.

Crypto is about giving you greater choice, independence, and opportunity. We are here to help you on your journey. We build crypto products that are simple, elegant, and secure. Whether you are an individual or an institution, we help you buy, sell, and store your bitcoin and cryptocurrency. 

At Gemini, our mission is to unlock the next era of financial, creative, and personal freedom.

In the United States, we have a flexible hybrid work policy for employees who live within 30 miles of our office headquartered in New York City and our office in Seattle. Employees within the New York and Seattle metropolitan areas are expected to work from the designated office twice a week, unless there is a job-specific requirement to be in the office every workday. Employees outside of these areas are considered part of our remote-first workforce. We believe our hybrid approach for those near our NYC and Seattle offices increases productivity through more in-person collaboration where possible.

The Department: Data

The Role: Head of Data

As the leader, you’ll shape the way we approach data at Gemini by creating a strategic vision for how data can help drive our business growth. You will build and manage a high-performance machine learning, data engineering, platform, and analytics team and leverage your experience and communication skills to work across business teams to develop innovative data solutions.  You will inspire and mentor a strong data team through your passion for data and its ability to transform decision-making and generate solutions for this new, exciting asset class. Communicating your insights and driving new product development across the organization is paramount to success. You will also be looked upon to share Gemini’s data vision and products externally.

Responsibilities:

• Lead team responsible for scaling our data infrastructure and optimizing our warehouse’s performance
• Lead design, architecture and implementation of best-in-class Data Warehousing and reporting solutions
• Define and drive the vision for data management, analytics, and data culture
• Collaborate with executive leadership to integrate data initiatives into business strategies
• Oversee the design, development, and maintenance of the company’s data platform, ensuring scalability, reliability, and security
• Lead and participate in design discussions and meetings
• Oversee the end-to-end management of our data ecosystem, ensuring data integrity, and driving data-driven decision-making across the organization including our products
• Design, automate, build, and launch scalable, efficient and reliable data pipelines into production
• Drive the development of advanced analytics, reporting solutions, and dashboards to provide actionable insights to stakeholders
• Oversee design, development,  and maintenance of ETL processes, data warehouses, and data lakes
• Research new tools and technologies to improve existing processes
• Implement best practices for data modeling, architecture, and integration across various data sources
• Develop new systems and tools to enable the teams to consume and understand data more intuitively
• Partner with engineers, project managers, and analysts to deliver insights to the business
• Own responsibilities around root cause analysis, production and data issues such as validation

Minimum Qualifications:

• 12-20+ years experience in data engineering with data warehouse technologies
• 5-7+ years experience bringing a data infrastructure to the next level including the overhaul of data, pipelines, architecture and modeling
• 10+ years experience in custom ETL design, implementation and maintenance
• 10+ years experience with schema design and dimensional data modeling
• Experience building real-time data solutions and processes
• Experience building and integrating web analytics solutions
• Experience with AI/ML tools and techniques, including experience deploying machine learning models in production
• Strong knowledge of traditional and modern data tools and technologies, including SQL, Python, cloud platforms (AWS, Azure, GCP), and big data frameworks
• Experience with AI/ML tools and techniques, including experience deploying machine learning models in produ