info_outline XGoogle will be prioritizing applicants who have a current right to work in Singapore, and do not require Google's sponsorship of a visa. Minimum qualifications: Bachelor's degree or equivalent practical experience. 5 years of experience with one or more general purpose programming languages including but not limited to: Java, C/C++, Python, Objective C, JavaScript, or Go. 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture. Preferred qualifications: Master's degree or PhD in Computer Science, or a related technical field. 3 years of experience designing, building, and maintaining large-scale data processing systems or data platforms. Experience with distributed systems, data warehousing, and big data technologies. Experience with Google's internal data technologies. Experience with Payment products. About the job Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. The GPay+Wallet Data Platform (GDP) team is building the foundational infrastructure and data applications designed specifically to power advanced analytics, AI personalization and agentic experiences. Our mission is to unlock the full potential of Payments data for Google by providing reliable, compliant, and scalable data infra. GDP fuels everything from advanced analytics and experiment measurement to the creation of targeting signals and crucial inputs for AI/ML models. As a Senior Software Engineer, you will play a key role in designing, building and evolving the core data infrastructure and tooling that underpins decision-making and product development within consumer payment. You will own technical areas, driving projects from ambiguous requirements to well-scoped, high-quality solutions, enhancing our self-serve data platform capabilities, empowering teams to effectively leverage payments data. Whether it is paying online with Autofill, using tap and pay in stores, or using the Google Pay app, the Payments team at Google is focused on making payments simple, seamless, and secure. In addition to consumer payment technologies, the Payments team also powers the money movement between Google and its consumers and businesses. Responsibilities Design, develop, and implement highly scalable and reliable data pipelines and infrastructure. Take full ownership of complex technical problems, from ideation and research to proposing and delivering end-to-end solutions, often involving ambiguous requirements. Drive technical strategy and best practices for data ingestion, processing, storage, and consumption, ensuring data quality, compliance (e.g., data localization, privacy), and discoverability. Collaborate closely with Product Managers, Data Scientists, Analysts, and Feature Engineering teams to understand data needs and deliver robust data solutions that meet business requirements. Identify opportunities to improve system efficiency, reliability, and developer experience within the data platform, proactively addressing technical debt and implementing optimizations. Advocate for and implement best practices in data infrastructure, software development, testing, and monitoring to ensure the reliability, scalability, and efficiency of GDP's systems.