Senior Staff Software Engineer, Google Cloud Business Platform
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development, and with data structures/algorithms.
- 5 years of experience with test automation, release management, SDLC management for enterprise software products.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 5 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- Experience with release and launch readiness, test frameworks, and SDLC management.
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.
As a Senior Staff Software Engineer, you will define the multi-year technical strategy and architectural roadmap for Google Cloud Business Platform's (GCBP) pre-production environments and automated testing ecosystems. You will advocate for the transformation of our environment landscape, moving from manual, fragmented staging environments to fully automated, hermetic, and time-accelerated pre-production layers.
In this role, you will work with leaders in GCBP, Ordering, Billing, and SAP/Finance to establish quality gates that safeguard high-stakes migrations and production releases. You will be a versatile technical leader who models engineering excellence, grows on solving highly ambiguous systems problems, excellent in SDLC management and communication and is passionate about mentoring and scaling a global engineering organization.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Define the multi-year architectural outook and strategy for GCBP’s pre-production environments, testing platform and SDLC management. Execute on the defined strategy with AI Agentic innovation.
- Drive the design, execution, and release governance of a brand new testing environment for the entire Google Cloud Platform (GCP) Lead to Cash systems. Establishing a reliable, fully connected end-to-end testing environment operating on a unified data plane with first-party and third-party systems.
- Partner with engineering and business stakeholders to define and enforce enterprise grate automated gatekeeping strategies (including presubmit integrations and release certification) to reduce production support tickets and outages.
- Mentor, grow, and provide technical direction to a high-performing global engineering team, fostering a culture of engineering excellence and influencing best practices and AI transformation across the organization.
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