Minimum qualifications: Bachelor's degree in Computer Science, Engineering, Mathematics, a related technical field, or equivalent practical experience. 3 years of experience working with data infrastructure and data models by writing exploratory queries and scripts. 3 years of experience in data engineering, database querying (e.g., SQL), and developing data pipelines (Extract, Transform, and Load (ETL) with Python). Experience with database administration techniques or data engineering, as well as writing software in Java, C++, Python, Go, or JavaScript. Preferred qualifications: Master's degree in Computer Science, Engineering, Mathematics, or a related technical field Experience troubleshooting live, high-traffic data pipelines during critical ETL operations. Experience developing applications used within law firms, in-house legal/compliance departments, government, or related industry experience. Experience using AI technologies to augment, improve, or automate the development process. Experience connecting agents to enterprise knowledge bases and enhancing Retrieval-Augmented Generation (RAG). Ability to be flexible/adaptable in exercising judgment in a dynamic environment and to prioritize and manage tasks efficiently. About the job As a Data Engineer within the Business Intelligence Group, you will partner with data science, analyst, and engineering teams to build and scale durable data products that enable a more data-driven/predictive Global Affairs (GA) organization. Translating complex business requirements into technical solutions, you will architect innovative data pipelines and infrastructure that accommodate complex ETL, volume, and latency constraints. With Generative AI (GenAI) poised to make a significant impact in GA, your goal is to leverage Google's tools and ML/AI ecosystems to move and translate data used for critical, cross-global affairs strategic decisions. In this fast-paced environment, you will independently execute end-to-end tasks to build scalable infrastructure that automates systems, improves user experiences, and directly enables AI-driven business decisions at scale. Responsibilities Design, build, deploy, and improve elegant, scalable, and modern data pipelines using standard and Google-specific database technologies, which may include building pipelines to aggregate data from multiple sources or enhancing the performance of existing pipeline tools and services. Make technical contributions including writing and reviewing design documents, tests, and code (e.g., Python, SQL, configurations) while identifying dependencies and resolving issues to drive implementation. Provide subject-matter expertise and utilize comprehensive knowledge of Google's relevant database technologies, principles, practices, and coding standards. Support the development and implementation of data driven web applications, with a focus on application interfaces that connect users to LLM APIs, to address business problems in Global Affairs, including providing trusted advice to policymakers, building an industry leading regulatory and compliance system, and protecting our ability to provide high quality products.