Senior Data Platform Engineer

Gemini

Senior Data Platform Engineer automating reliable databases and data infrastructure for Gemini, a global crypto and Web3 platform. Building self-service provisioning, scaling, failover, observability, and SRE tooling across diverse datastore technologies.

Posted 8/4/2026full-timeFlorida, New York • 🇺🇸 United StatesSenior💰 $126,000 - $180,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in managing and scaling relational databases such as PostgreSQL and Amazon Aurora, with a strong focus on automation, Infrastructure as Code, and CI/CD practices. Proficient in integrating data pipelines and ensuring high availability through effective monitoring and incident response.

Highest-signal resume keywords

PostgreSQL ManagementAmazon Aurora ExpertiseInfrastructure as Code (Terraform)CI/CD ImplementationData Pipeline Integration (Kafka)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Database ProvisioningReplicationFailoverBackup/RecoveryPerformance TuningAutomationScripting (Python, Go)Monitoring and AlertingHigh-Availability ArchitectureNoSQL Databases

Soft Skills

Strong CommunicationCollaboration

Tools & Technologies

AWS RDSRedshiftEMRGoogle BigQueryDatabricks

Industry Keywords

Infrastructure as CodeSelf-Service ToolingSLOsError BudgetsIncident Response

Tech Stack

Tools & technologies

Amazon RedshiftAWSBigQueryETLGoKafkaNoSQLPostgresPythonTerraform

About the role

Key responsibilities & impact

Build Infrastructure as Code, CLI tools, and CI/CD-driven automation for self-service database provisioning, scaling, failover, and deployment.
Serve as the team's relational database specialist for Amazon Aurora and PostgreSQL, covering replication, failover, backup/recovery, and performance.
Extend operational tooling and guardrails across document, key-value, columnar, and other datastore systems.
Define and track SLOs and error budgets, build monitoring and alerting, implement high-availability architectures, and participate in on-call rotations.
Integrate with real-time and batch data pipelines using Kafka, ETL workflows, and processing frameworks.
Identify and resolve query- and infrastructure-level performance bottlenecks and reduce MTTR.
Automate repetitive operational work and contribute to documentation, incident retrospectives, and platform playbooks.
Collaborate with infrastructure, data engineering, and product engineering teams.

Requirements

What you’ll need

5 years of experience in the field
Specialist-level experience managing and scaling PostgreSQL, Amazon Aurora, or similar relational databases
Experience with replication, failover, backup/recovery, and query/engine performance tuning
Experience building automation, self-service tooling, and guardrails for database operations
Production experience with at least one non-relational paradigm, such as NoSQL, columnar, document, or key-value databases
Familiarity with AWS RDS, Redshift, EMR, Google BigQuery, or Databricks
Experience with Infrastructure as Code, specifically Terraform
Ability to write scripts, CLIs, or services in languages such as Python or Go
Understanding of CI/CD, observability tooling, SLOs/error budgets, and production incident response
Experience integrating data pipelines and real-time messaging systems such as Kafka or Kinesis
Ability to participate in on-call rotations and own uptime and recovery responsibilities
Strong communication and collaboration skills across infrastructure, data, and product teams

Benefits

Comp & perks

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
Remote work flexibility for employees who do not live near one of the company hubs
In-person collaboration at hub offices under the hybrid work approach