IT staffing and managed services with data engineering depth
Burgeon IT Services is a staffing and managed operations provider positioned across technical hiring, payroll administration, and application development. The tech stack reveals a data engineering–heavy internal operation: Azure cloud infrastructure paired with Python/Spark/Airflow for ETL, Databricks for analytics, and ML frameworks (TensorFlow, PyTorch, scikit-learn) — stack depth that signals Burgeon is not just placing consultants but running sophisticated internal data pipelines for client delivery and analytics. Active hiring skews senior engineering roles across Australia, US, Canada, and Vietnam.
Burgeon IT Services provides contract, contract-to-hire, direct hire, and payroll services to companies of all sizes. Founded in 2010, the company operates across the United States, Australia, and India, with headquarters in Claymont, Delaware. Core services include IT staff augmentation, talent acquisition, and managed operations (payroll, accounting, bookkeeping). Active projects span network intelligence modeling, geospatial marketing analytics, manufacturing execution systems (Tulip MES), and real-time production monitoring — indicating expansion beyond staffing into domain-specific advisory and implementation services. Internal pain points center on GMP compliance, system availability, incident response time, and data quality optimization across large datasets.
Primary stack: Azure (cloud), Power BI (BI), Databricks (analytics), Python, Apache Airflow, Apache Spark, TensorFlow, PyTorch. Also uses AWS (SageMaker, Redshift, Athena), GCP, and infrastructure-as-code tools (Terraform, CloudFormation, AWS CDK).
Claymont, Delaware. Founded 2010, privately held, 51–200 employees. Operations also in Australia and India.
BURGEON IT SERVICES'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.