Software Engineer, Global Advertising Data Platform

关于这个机会

Team Introduction The Global Advertising Data Platform team builds the data foundation and products behind advertising across our international products — petabyte-scale ingestion and storage through to the query and data products thousands of internal users and systems depend on every day. The team is dedicated to making an AI-native data platform that enables agents to be reliable colleagues across all data-related scenarios. Semantic modeling, compile-time governance, agent-facing services and tools, evaluation infrastructure, all at global advertising scale. The work is measured by what it delivers: a better advertiser experience, efficiency lift, measurable business growth, or strategy that lands quickly with the platform's help. Responsibilities - Design and build the core of an AI-native data platform: Own architecture and hands-on development of high-throughput services serving hundreds of millions of users' advertising activity. You will take up versatile roles and deliver solutions end to end: Identify and define the problem, design technical solutions, build the system with agents, tune and optimize the outcome. - Design agent-facing data services and tool interfaces: Build the APIs and tool surfaces (MCP-style typed interfaces, retrieval over catalog and metadata, structured query execution) through which agents discover and use data — with scoped permissions, typed inputs, and full audit trails, so capability and safety ship together. - Contribute to the semantic layer that makes data agent-consumable: Turn tribal knowledge into machine-readable definitions: metrics, dimensions, lineage, valid join paths, and data contracts, etc. This is the core that decides whether an agent's data work is stable, reliable and verifiable. - Make correctness measurable: Contribute to code and testing standards and to the quality control methods the team runs on — extended to a world where both humans and models write code and generate queries. Build golden query suites, regression and evaluation harnesses, lineage-based impact analysis, and data quality monitoring that catch semantic drift before users do. - Conquer technical challenges: High concurrency, multi-tenant data isolation and governance enforced at query-generation time rather than patched afterwards, system decoupling, cost and performance at scale — these are the recurring challenges of the platform, and you'll work with the team to break through them.

任职要求

Minimum Qualifications - Bachelor's degree in Computer Science or a related discipline. - Genuine interest in computer science and internet technology, with strong command of at least one programming language — including but not limited to Java, C, C++, Python, or Go. - Solid computer science fundamentals: data structures, algorithms, operating systems, databases and computer networks. - Strong analytical thinking — able to abstract and decompose messy business logic into clean system boundaries. - Comfortable using AI coding agents as part of how you build, together with the judgment to review, test, and take responsibility for what they produce. - Strong drive to learn, and the communication skills to work across engineering, product, and analytics. Preferred Qualifications - Experience with big data or distributed systems technologies such as Spark, Flink, Kafka, Iceberg/Hudi, ClickHouse, Presto/Trino, or similar. - Hands-on experience building applications on large language models — RAG, agent frameworks, tool/function calling, natural-language-to-SQL, or model evaluations. - Familiarity with data warehousing and modeling practice: dimensional modeling, metric/semantic layers, dbt, data lineage, or data catalog and governance tooling. - Open-source contributions, research publications, competitive programming or data competition results, or substantial personal projects. - Prior internship or project experience in advertising technology, recommendation systems, or large-scale data analytics.

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