InOrg is a consulting firm built around cloud infrastructure and data engineering, with a tech stack spanning AWS, Azure, GCP, Kubernetes, and the full ELK observability suite. Active projects center on CI/CD pipeline architecture, IaC implementation, and legacy ETL-to-Databricks migrations—signaling deep engagement with clients modernizing data platforms. The hiring mix (engineering-heavy, mostly senior-level) and adoption of Databricks suggest the firm is positioning itself as a hands-on transformation partner, not just an advisory shop.
InOrg helps mid-market organizations design and implement cloud infrastructure and data engineering transformations. The company is based in Charlotte, NC and operates at 51–200 employees. Their consulting engagements span DevOps maturity assessments, CI/CD pipeline architecture, infrastructure-as-code rollouts, and data platform migrations—particularly Databricks implementations and Microsoft Fabric end-to-end data solutions. The project portfolio reflects a focus on solving deployment bottlenecks, data lineage challenges, and the shift from batch ETL to modern cloud-native patterns.
InOrg operates across AWS, Azure, GCP, Kubernetes, Docker, Terraform, Ansible, Jenkins, GitLab, ELK stack (Elasticsearch, Logstash, Kibana), SQL Server, .NET/ASP.NET, and Python. The firm is actively adopting Databricks for data platform work.
Current projects include CI/CD pipeline architecture, infrastructure-as-code implementation, DevOps practice design, Databricks and AI/ML migrations, and Microsoft Fabric-based end-to-end data solutions. The firm is also addressing data lineage and regulatory compliance challenges for clients.
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InOrg Global'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.