Minimum qualifications:

• Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
• 8 years of experience in software development, including large-scale data systems or information retrieval.
• Experience with programming in C++, Java, Python, or Go.
• Experience designing and maintaining data pipelines.

Preferred qualifications:

• Understanding of the Search product landscape and its unique data issues (e.g., latency, richness, quality).
• Track record of leading organization-wide technical debt reduction or metrics convergence projects.
• Ability to navigate a matrixed organization and drive alignment across cross-functional teams.

About the job

In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.

The US base salary range for this full-time position is $207,000-$300,000 + 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.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google

Responsibilities

• Own the data engineering strategy for high-stakes Search initiatives, designing multi-stage data products that process data for billions of users.
• Architect organization-wide initiatives for metrics convergence to establish single-source-of-truth foundations for operational and topline Search metrics.
• Integrate core data systems with Google's backend infrastructure, ensuring technical designs are optimized for both massive scale and low-latency consumption.
• Collaborate with Product Data Scientists and Engineering leads to identify growth and quality opportunities, bridging the gap between raw data and actionable insights.
• Act as a primary technical advisor to Search leadership, transforming ambiguous product goals into solid architectural decisions.