Staff augmentation and cloud operations for enterprise infrastructure
Pearster staffs large organizations with distributed engineering talent across Latin America, Europe, and the Philippines, focusing on infrastructure, DevOps, and cloud migrations. The tech stack—heavy on Terraform, Kubernetes, and Snowflake alongside network infrastructure (Cisco, Palo Alto)—reveals internal capability in complex deployments. Active hiring is concentrated in engineering and ops roles, with a 50/50 mid/senior split, matching their project load: migrating 1,000 data pipelines to Snowflake, moving legacy e-commerce platforms to Wix, and implementing IaC automation across Azure and multi-cloud environments.
Pearster is a staff augmentation and managed services firm founded in 2020, helping mid-market and enterprise organizations close talent gaps in cloud infrastructure, DevOps, and machine learning. The company operates across Latin America (Argentina, Brazil, Colombia, Mexico), Europe, and the Philippines, providing team extensions and consulting services without traditional recruitment overhead. Their service delivery model centers on infrastructure-as-code, cloud platform migrations, and operational scalability—reflected in current engagement around large-scale data pipeline consolidation, e-commerce platform modernization, and cost optimization in cloud environments.
Pearster sources engineers and operations staff from Latin America (Argentina, Brazil, Colombia, Mexico), Europe, and the Philippines. Their business model focuses on distributed, borderless talent pools for client team extensions.
Core tools include Terraform, Ansible, Kubernetes, Docker, Jenkins, and GitLab for infrastructure and CI/CD. Data layer: Snowflake, Kafka, Talend. Monitoring: Datadog, Prometheus, Grafana, New Relic. Network: Cisco, Palo Alto Networks, F5 BIG-IP.
Major projects include migrating 1,000 data pipelines to Snowflake, moving legacy e-commerce platforms to Wix, deploying infrastructure-as-code via Terraform, Azure cloud operations, and optimizing cloud cost visibility and efficiency.
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Pearster's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.