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Overview
Join Gemini as a Senior Data Platform Engineer, focusing on the reliability and automation of our data infrastructure. Work with cross-functional teams to build self-service, automated foundations for data management. 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.
Responsibilities
- •Automation and Reliability Engineering: Build Infrastructure as Code (IaC), CLI tools, and CI/CD-driven automation that make database provisioning, scaling, failover, and deployment self-service, consistent, and repeatable across environments - this is the core of the role, not a supporting activity.
- •Database Scaling and Optimization: Serve as the team's depth on relational database systems (e.g., Amazon Aurora, PostgreSQL) - replication topologies, failover, backup/recovery, and query/engine-level performance - ensuring high performance and availability under growing workloads.
- •Fleet-Wide Infrastructure Design: Extend that operational rigor to the rest of the datastore fleet - document, key-value, and columnar systems - applying the right paradigm to the right workload and building common tooling and guardrails across all of them.
- •High Availability, Observability, and SRE Practice: Define and track SLOs/error budgets, build proactive monitoring and alerting, implement high-availability architectures, and participate in the on-call rotation to troubleshoot and resolve production issues quickly.
- •Pipeline Integration: Collaborate with data and product engineering teams to integrate with upstream and downstream pipelines - both real-time and batch - via message queues (e.g., Kafka), ETL workflows, and processing frameworks.
- •Performance Tuning and Troubleshooting: Identify and resolve performance bottlenecks at both the query and infrastructure levels across engines. Establish alerting, observability, and incident response procedures that reduce MTTR and maintain service health.
- •Toil Reduction and Operational Excellence: Continuously identify and automate away repetitive operational work; contribute to shared documentation, incident retrospectives, and platform playbooks to improve team effectiveness and reliability of operations.
The compensation & benefits package for this role includes
- •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
Salary Range: 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.
Requirements
- •5 years of experience in the field.
- •Deep, specialist-level experience managing and scaling relational databases - cloud-native systems like PostgreSQL, Amazon Aurora, or similar - including replication, failover, backup/recovery, and query/engine performance tuning.
- •Demonstrated SRE mindset: experience building automation, self-service tooling, and guardrails that eliminate manual, repetitive database operations rather than performing them by hand.
- •Hands-on experience with at least one non-relational paradigm in production (e.g., NoSQL, columnar, document, key-value), and working knowledge of when to apply each.
- •Familiarity with cloud-based data platforms and services such as AWS RDS, Redshift, EMR, Google BigQuery, or Databricks.
- •Experience in an infrastructure as code environment (Terraform), developing automated solutions to solve support and operational issues.
- •Proficiency writing scripts, CLIs, or services that increase developer productivity and reduce operational toil, in languages like Python, Go, etc.
- •Understanding of CI/CD, observability tooling, SLOs/error budgets, and incident response in production environments.
- •Experience integrating with data pipelines and real-time messaging systems like Kafka or Kinesis.
- •Comfortable participating in on-call rotations and owning uptime and recovery responsibilities across multiple database technologies.
- •Strong communication and collaboration skills; able to work effectively across infrastructure, data, and product teams.