Enterprise IT and mechanical engineering services for automotive suppliers
Shaarpro blends automotive mechanical engineering (actuator design for vehicle systems) with enterprise IT infrastructure work (cloud migrations, Oracle Financials implementation, domain consolidation). The stack—CATIA for CAD, Zebra for industrial systems, multi-cloud (Azure, AWS, GCP), Kubernetes, and Databricks—reflects a hybrid business serving both manufacturing and IT operations functions. Active hiring skews senior (3 of 5 roles), concentrated in engineering and security, suggesting either customer delivery intensity or internal capability maturation.
Shaarpro is a 51–200 person services firm headquartered in East Brunswick, New Jersey, operating across automotive engineering and enterprise IT consulting. On the mechanical side, they develop actuators and motorized systems for vehicle features—chargeport doors, mirrors, tonneau covers, glazing—targeting automotive OEM and supplier customers. On the IT side, they handle cloud infrastructure work, tenant migrations, domain consolidation, and financial systems implementation (Oracle Fusion). The company maintains a polyglot tech stack (Java, Go, Python, JavaScript) and deploys across Azure, AWS, and GCP, indicating customer-driven multi-cloud commitments.
CATIA, Java, Go, Python, JavaScript, Azure, AWS, GCP, Kubernetes, Docker, Terraform, Databricks, Apache Spark, Oracle Fusion Financials, Azure DevOps, Splunk, Jira, and Cadence Allegro for CAD work.
Actuator development for automotive systems (chargeport doors, mirrors, tonneau covers, glazing), tenant-to-tenant cloud migrations, domain consolidation, Oracle Fusion Financials implementation, and email compliance retention policies.
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Shaarpro'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.