Staff Software Engineer, Analytics

Google Google · Big Tech · Bengaluru, Karnataka, India

Staff Software Engineer, Analytics at Google, focusing on data platforms for Google One and Google Photos. The role involves owning technical strategy, architectural decisions for multi-quarter initiatives impacting financial compliance and AI data strategy, and designing high-performance solutions for scaling bottlenecks. Requires extensive experience in C++, software development, large-scale infrastructure, and data analytics.

What you'd actually do

  1. Own the technical strategy and outcomes for the Analytics data platforms that power Google One (G1) and Google Photos. Navigate high levels of ambiguity to drive architectural decisions for multi-quarter initiatives that impact financial compliance, AI data strategy, and infrastructure scalability.
  2. Own the long-term technical strategy and outcomes for complex, multi-quarter data platform initiatives that support global consumer products and large-scale user bases. Clarify and make tractable large, ambiguous technical problems where high-level solutions are not yet defined, translating broad business needs into scalable architectural goals.
  3. Act as the primary architect for data ingestion from different internal products and privacy frameworks, ensuring secure and standardized data handling across major strategic partner surfaces.
  4. Identify, and resolve scaling bottlenecks by designing high-performance solutions.

Skills

Required

  • C++
  • software products
  • large-scale infrastructure
  • distributed systems
  • networks
  • compute technologies
  • storage
  • hardware architecture
  • software design
  • architecture
  • big data
  • data analytics
  • SQL
  • object-oriented analysis and design
  • SQL pipelines

Nice to have

  • Master’s degree or PhD in Engineering, Computer Science, or a related technical field
  • data structures and algorithms
  • technical leadership role
  • complex, matrixed organization
  • cross-functional, or cross-business projects

What the JD emphasized

  • AI data strategy