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. 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. 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. The Role: Staff Data Platform Engineer The Data Platform Engineering team provides the foundation upon which all analytics, ML, and data-driven products are built. As a Staff Data Platform Engineer, you will own and evolve our data warehouse infrastructure (Databricks, AWS resources, storage layers, orchestration tools, and security). You will lead efforts in cost optimization, governance, access management, and tooling — ensuring that our data platform is scalable, reliable, secure, and cost-efficient. This is a senior IC role where you will influence architectural direction across the data org, mentor other engineers, and drive best practices in platform engineering and governance. This role is required to be in person twice a week at either our New York City, NY or San Francisco, CA office. Responsibilities: <ul> <li>Own the design, build, and operate data infrastructure, including Databricks &amp; AWS</li> <li>Define standards for storage, compute, orchestration, and metadata management to support analytics, data engineering, and ML use cases</li> <li>Lead architecture and design for cross-team data platform initiatives, ensuring scalability, resiliency, and performance</li> <li>Monitor &amp; forecast data platform infrastructure and costs, proactively identifying opportunities for workload optimizations</li> <li>Partner with security, compliance, and legal teams to meet regulatory requirements and enforce data governance policies</li> <li>Implement and manage fine-grained access management, role-based access control (RBAC), attribute-based access control (ABAC), and row/column-level security</li> <li>Drive adoption of metadata management, catalogs, and lineage tooling</li> <li>Build reusable tooling and frameworks for data engineers and analysts (e.g., templated pipelines, schema migration tools, observability dashboards)</li> <li>Partner with SREs / DevOps to harden environments and implement disaster recovery</li> <li>Serve as a technical leader and subject matter expert across the data org, influencing standards and best practices</li> <li>Mentor senior data platform engineers, conduct design and code reviews, and guide cross-functional platform initiatives</li> </ul> Minimum Qualifications: <ul> <li>8+ years of experience in data engineering, platform engineering, or infrastructure engineering, with at least 3+ years focused on platform-level responsibilities</li> <li>Strong hands-on experience with Databricks (clusters, jobs, delta lake, Unity Catalog) and AWS data services (S3, Glue, EMR, Athena, IAM)</li> <li>Deep knowledge of data warehouse and lakehouse architectures (Airflow, ETL, Delta, Parquet)</li> <li>Strong programming experience with Python, SQL, and infrastructure-as-code frameworks</li> <li>Proven track record in cost optimization, spend visibility, and scaling cloud-based data workloads</li> <li>Experience with data governance, security, and access management (RBAC/ABAC, encryption, auditing)</li> <li>Strong understanding of reliability, monitoring, and observability for distributed data systems</li> <li>Demonstrated ability to influence cross-team architecture and mentor other engineers</li> </ul> Preferred Qualifications: <ul> <li>Familiarity with blockchain / crypto / Web3 data (e.g., running indexing infrastructure, managing chain APIs, or operating large-scale node infrastructure)</li> <li>Experience with enterprise data catalog and governance platforms</li> <li>Experience with advanced access control frameworks (row-level, column-level, tokenized access)</li> <li>Exposure to ML platform components (feature stores, model registries) or AI/LLM workloads (vector databases, embedding pipelines)</li> <li>Knowledge of networking, VPC design, and data replication patterns</li> <li>Experience managing compliance-heavy data environments (SOX, HIPAA, PCI DSS, GDPR, etc.)</li> <li>Strong performance tuning skills at both infrastructure and query level</li> </ul> <div>It Pays to Work Here</div> <div> </div> <div>The compensation &amp; benefits package for this role includes:</div> <ul> <li>Competitive starting salary</li> <li>A discretionary annual bonus</li> <li>Long-term incentive in the form of a new hire equity grant</li> <li>Comprehensive health plans</li> <li>401K with company matching</li> <li>Paid Parental Leave</li> <li>Flexible time off</li> </ul> Salary Range: The base salary range for this role is between $168,000 - $240,000 in the State of New York, the State of California and the State of Washington. 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. 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, so candidates are encouraged to connect with their recruiter to learn more about the specific policy for the role. Employees who do not live near one of our hubs are part of our remote workforce. At Gemini, we strive to build diverse teams that reflect the people we want to empower through our products, and we are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Equal Opportunity is the Law, and Gemini is proud to be an equal opportunity workplace. If you have a specific need that requires accommodation, please let a member of the People Team know. #LI-PA1

Gemini

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