IT staffing and consulting firm with deep data engineering and enterprise AI practice
TMF is a national IT staffing and consulting firm founded in 1976, now heavily invested in data platforms and AI. The tech stack reveals a shift toward data operations and ML: Snowflake, dbt, Kafka, Spark Streaming, Databricks, and MLflow dominate, paired with Oracle and AWS infrastructure. Current hiring is tilted toward senior data and engineering roles, and active projects span DataOps standardization, streaming pipelines, and agentic AI—indicating TMF is positioning itself beyond traditional staffing into embedded data and AI consulting for enterprise clients.
TM Floyd & Company serves mid-market and enterprise clients across education, government, energy, automotive, manufacturing, financial services, and healthcare. The firm combines IT staffing (placement of developers, engineers, and IT professionals from junior to executive level) with consulting and contracting services. Operating from Columbia, SC with 51–200 employees, TMF addresses client technology and operational challenges while building talent pipelines for IT professionals. Recent work centers on data engineering (pipelines, governance, quality), cloud modernization, and machine learning—signaling a transition from pure staffing toward retained consulting engagements and specialized practice areas.
Snowflake, Oracle (Exadata, Cloud HCM, ERP, EPM), AWS, Kafka, Spark Streaming, dbt, Python, Databricks, Azure Machine Learning, Power BI, and Informatica. Stack favors modern data platforms and cloud infrastructure.
DataOps standardization, scalable batch and real-time streaming pipelines, data governance and quality frameworks, ML solutions for asset health and predictive maintenance, forecasting pipelines, and agentic AI proof-of-concepts—primarily for enterprise and regulated-industry clients.
TM Floyd & Company (TMF)'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.