Software Engineer III, BigQuery

About the job

Google Cloud's software engineers develop the next‑generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast‑paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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.

Big Query brings the power of distributed computing to data science, data engineering and AI/ML workflows, all at Big Query scale. By providing a familiar pandas and scikit‑learn experience, it enables users to analyze and model massive datasets exactly where they reside—directly in Big Query. From performing data exploration, running a Large Language Model (LLM) on huge datasets for insights, to creating a ML model for sentiment analysis at Terabyte (TB) scale.

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.

The US base salary range for this full‑time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job‑related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents‑to‑be, criminal histories consistent with legal requirements, or any other basis protected by law.

See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

• Health, dental, vision, life, disability insurance
• Retirement Benefits: 401(k) with company match
• Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
• Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
• Maternity Leave (Short‑Term Disability + Baby Bonding): 28‑30 weeks
• Baby Bonding Leave: 18 weeks
• Holidays: 13 paid days per year

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development or 1 year of experience with an advanced degree in an industry setting.
• 2 years of experience with developing large‑scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
• Experience querying and analyzing datasets using Big Query.

• Experience with scripting languages such as Python.
• Experience with Cloud Run and virtualization.
• Knowledge of computer science, with strong competencies in data structures, algorithms, and software design.

Feature design, including writing high quality design documents, and driving approvals.

• Make your feature operation simple and scalable. This includes monitoring dashboards, doing deployments and keeping production playbooks up to date.
• Monitor and gather intelligence over feature utilization and issues.
• Help customers with debugging and addressing reasonable requests quickly, which includes responding to them on multiple channels.
• Manage coding that includes great test coverage and production stability.