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
- Act as a trusted technical advisor to customers and solve complex big data challenges.
- Create and deliver best practice recommendations, tutorials, blog articles, sample code, and technical presentations, tailoring approach and messaging to varied levels of business and technical stakeholders.
- Analyze on-premises and cloud database environments and consult on the optimal design for performance and deployment on Google Cloud Platform.
- Travel regularly up to 30% of the time, in-region for meetings, technical reviews, and onsite delivery activities.
- Communicate effectively via video conferencing for meetings, technical reviews, and onsite delivery activities.
Qualifications
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.