Digital and intelligent technology services for the oil and gas industry
Kunlun Digital Technology, a CNPC subsidiary, builds software for energy operations, with drilling optimization and wellbore accident prevention as recurring themes in its job posts. Its stack pairs big-data tooling (Spark, Flink, Kafka, Hadoop) and the WITSML wellsite data standard with robotics frameworks (ROS, Gazebo, rviz). Senior-heavy, engineering-led hiring is accelerating, alongside finance work tied to IPO compliance.
Kunlun Digital Technology Co., Ltd. is a Beijing-headquartered public company founded in 2006 and operating as a subsidiary of CNPC. It provides digital and intelligent technology across the full delivery cycle for the energy sector: consulting, design, R&D, implementation and ongoing operations. Its offerings include SAP ERP services, drilling software, remote geological analysis and oil and gas digitalization solutions. The company employs between 5,001 and 10,000 people and hires in China.
Its stack includes Python, Java and Go, plus Apache Spark, Flink, Kafka, Hadoop and TensorFlow for data and AI. It also uses ROS, Gazebo and rviz for robotics, WITSML for drilling data, and Vue, TypeScript and uni-app on the front end.
Job posts point to drilling software development, remote geological analysis, robot product architecture, oil and gas digitalization solutions, Xinchuang alternative technology R&D, and a new financial analysis system.
Yes. Hiring is accelerating and is mostly in engineering, with a senior-heavy mix. There are also openings in sales, security, finance and operations, all based in China.
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Kunlun Digital Technology Co., Ltd.'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.