Teza is a systematic quantitative investment manager running 24/7 trading operations across multiple asset classes and time zones. The tech stack reveals a data-engineering-heavy organization: Python, C++, PostgreSQL, MongoDB, Hadoop, Airflow, Kubernetes, and Redis form the backbone, with heavy infrastructure automation (Ansible, Salt, Docker) and observability tooling (Grafana, Icinga, Nagios). Active hiring in engineering and data roles, combined with projects around data warehouse expansion, unified release pipelines for strategies, and self-service compute orchestration (Slurm/Hadoop/Airflow), signals scaling toward automation and reducing manual trading operations.
Teza operates a quantitative investment management business, executing algorithmic trading strategies across global markets with holding periods ranging from milliseconds to months. Based in Chicago with offices across six time zones, the firm trades continuously and employs roughly 50–200 people, with roughly half in engineering and data roles. The company is privately held and was founded in 2009. Operations span systematic strategy development, infrastructure automation, and data pipeline management; recent focus areas include automated data cleansing, warehouse expansion, release pipeline standardization, and improving observability across trading and operational systems.
Primary languages are Python and C++, alongside Java and Bash/Zsh for scripting. The stack reflects a split between data transformation (Python, NumPy, Pandas) and high-performance quantitative computing (C++).
On-premise and cloud hybrid: RHEL/Debian, VMware, Docker, Kubernetes, AWS, and GCP. Compute orchestration spans Slurm, Hadoop, and Apache Airflow. Observability is built on Grafana, Icinga, and Nagios.
Teza Technologies'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.