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Data Platform Architect (Center Lead)
A Low-altitude Economy Big Data Company
Responsibilities
- Lead the overall architecture design, technical roadmap, and evolution planning for enterprise-level data platforms / data middle platforms.
- Design the full-link architecture spanning data collection → cleaning → storage (Lakehouse ODS / DWD / DWS / ADS) → computation → service enablement, supporting PB-scale multi-source heterogeneous data (images, point clouds, time-series, business data).
- Design edge preprocessing architectures for airborne / ground stations (compression, initial cleaning, breakpoint resume transmission) to ensure stable, low-latency drone-to-cloud connectivity.
- Establish data standards, governance frameworks, metadata management, data quality monitoring, and asset catalogs.
- Oversee technology selection, performance optimization, cost control, high availability, and private / localized deployment assurance.
- Build the AI engineering foundation for the data platform (service automation of labeling / quality inspection models; cutting-edge LLM research is handled by the AI R&D team), supporting internal algorithm and engineering teams.
- Collaborate with the AI R&D team, scenario application group, and business center to provide data capability support, ensuring government / enterprise platform-level delivery (multi-tenant, high availability), and guide data engineering / governance / platform / AI engineering teams.
Requirements
- Bachelor’s degree or above in Computer Science, Software Engineering, Mathematics, Statistics, or related fields; 8+ years of experience in data platform / data middle platform / big data architecture, including 5+ years of hands-on experience building data or AI platforms from scratch.
- Proficient in the Hadoop ecosystem (Spark / Flink / Kafka / HBase) and OLAP engines (ClickHouse / StarRocks / Doris); skilled in data warehouse modeling, data governance, lakehouse architecture, real-time computing, and data service methodologies; proven track record in handling PB-scale multi-source heterogeneous data.
- Familiar with cloud-native and distributed architectures; experienced in containerization (Docker / K8s), microservices design, and performance optimization; experience with major public clouds (e.g., AWS / Aliyun / Huawei Cloud) and private / cloud-hybrid deployments.
- Experience building AI PaaS / SaaS platforms from 0 to 1; familiar with MLOps toolchains (MLflow / Kubeflow); capable of encapsulating model capabilities into platform services (cutting-edge LLM research is handled by the AI R&D team).
- Prior experience in industry data platforms for surveying & mapping, remote sensing, HD maps, point cloud processing, embodied AI / robotics, or low-altitude economy is preferred.
- Strong technical leadership, cross-functional communication skills, and commercial acumen; complete experience delivering large-scale projects from inception to commercial deployment.
- 【Preferred Qualifications】
- Experience with UAV data acquisition and edge computing (device-cloud collaboration) platforms.
- Experience delivering large-scale government / enterprise platform projects (aligned with First Curve ToG requirements).
- Practical experience in AI engineering for data platforms (automated labeling, service-based quality inspection models).
About the company
We are a high-tech enterprise dedicated to promoting the application of UAV aerial remote sensing technology in smart cities, and a leading player in China's industrial UAV sector. The company has established an integrated upstream-and-downstream business system covering UAV airframe development, core avionics R&D, data acquisition, data mining, and application platform development and service promotion. By combining UAV aerial remote sensing and automatic remote sensing image processing technologies, GIS technology, and oblique photography 3D modeling technology, we build an air-ground integrated data acquisition and application system. We serve smart city operation agencies, providing accurate and efficient data support services to relevant decision-making departments.
- Industry
- AI Applications & LLMs
- Founded
- 2012-06-27