Senior Site Reliability Engineer

Globalstar•Covington, LA

About The Position

Globalstar is seeking a Senior Site Reliability Engineer to strengthen the reliability, performance, and on-call coverage of its large-scale monitoring and data platform, which provides real-time and historical visibility into satellite and ground infrastructure. This hands-on role spans infrastructure engineering, data-pipeline reliability, monitoring strategy, and operational excellence. The engineer will help scale monitoring and analytics capabilities while maintaining speed, cost efficiency, and dependability. The role includes owning the health and performance of a high-volume operational data pipeline; improving performance, cost efficiency, and scalability; evaluating and integrating monitoring, alerting, and data-platform tools; maintaining deterministic operational checks; contributing to incident response and disaster recovery; and partnering with stakeholders on workflows, capacity, and investment priorities. The engineer will also promote infrastructure-as-code and automated deployment practices and mentor colleagues to build shared platform knowledge. The position has no supervisory responsibilities. It may require travel, work outside regularly scheduled hours, prolonged computer use, and occasional lifting of up to 15 pounds. Reasonable accommodation may be made to enable individuals with disabilities to perform essential functions.

Requirements

At least 7 years in Site Reliability Engineering, Platform Engineering, Data Engineering, or a closely related discipline, operating production systems at meaningful scale.
Strong experience with modern data infrastructure, including streaming or event-driven data pipelines, large-scale storage systems, and analytical query engines.
Proficiency in at least one systems programming language, such as Go or Java, used for backend or data services.
Practical production experience with observability and monitoring tools for metrics, logs, traces, and alerting.
Demonstrated on-call experience, including incident response, root-cause analysis, and clear postmortem writing.
Comfort with infrastructure-as-code and modern CI/CD or GitOps practices.
Strong communication skills, including explaining technical tradeoffs to engineers and non-technical stakeholders.
Excellent verbal and written communication skills, including clear and concise interaction with all departments and levels of management.
Excellent organizational skills and attention to detail.
Ability to meet multiple deadlines in a fast-paced environment.
Ability to manage time effectively and prioritize tasks.
Ability to act with integrity, professionalism, and confidentiality.
Proficiency with Microsoft Office.
Familiarity with NetSuite.

Nice To Haves

Experience operating a large-scale data or monitoring platform, at multi-terabyte-per-day scale or higher.
Familiarity with multi-region or disaster-recovery architectures.
Familiarity with SQL database queries.
Familiarity with AWS data-pipeline tools such as S3, Kinesis, and Kinesis Analytics.
Background evaluating and integrating third-party or commercial monitoring or data-platform tools.
Experience in industries involving high-cardinality sensor, IoT, or infrastructure telemetry.

Responsibilities

Own the health and performance of a large-scale data and monitoring pipeline that ingests, stores, and serves high volumes of operational data.
Continuously improve system performance, cost efficiency, and scalability as data volume and usage grow.
Evaluate, adopt, and integrate open-source and commercial monitoring, alerting, and data-platform tools; assess build-versus-buy tradeoffs and lead pilots where useful.
Design and maintain rules-based, deterministic checks used by operational teams for critical alerting and data-quality assurance.
Lead or contribute to incident response, on-call rotations, root-cause analysis, and production-system postmortems.
Support disaster-recovery planning and execution, including regional failover exercises and recovery validation.
Assess workflows and data practices, identify gaps, and drive phased improvement plans with operations and other engineering teams.
Partner with engineering leadership and stakeholders to plan capacity, prioritize investments, and communicate tradeoffs in clear, non-technical terms when needed.
Champion infrastructure-as-code and automated deployment practices across the platform.
Mentor other engineers and build institutional knowledge so the platform is not dependent on any one individual.