Hiring: Senior Data Platform Engineer Company: Gemini Location: New York, NY Job Posted Time: 2026-09-16 13:15:37 Employment Type: Remote Target Skills & Keywords : AWS, Aurora, BigQuery, CI/CD, Data Pipeline, Databricks, EMR, ETL, IaC, Infrastructure as Code, Kafka, Kinesis, PostgreSQL, Python, RDS, REST, React, Redshift, Terraform, Web3 About the job Experience: •5 years of experience in the field. Required Skills: •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. Qualifications: •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. •Applied hands-on capability in at least one non-relational paradigm in production (e.g., NoSQL, columnar, document, key-value), and working knowledge of when to apply each. •Operational familiarity with cloud-based data platforms and services such as AWS RDS, Redshift, EMR, Google BigQuery, or Databricks. •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. •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. •It Pays to Work Here Compensation: •$126,000 - $180,000 / year •Flexible work environment (work from home / hybrid options) Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!