Principal Engineer, BigQuery Storage and Lakes

Minimum qualifications:

• Bachelor's degree in Computer Science, similar technical field of study, or equivalent practical experience.
• 15 years of professional experience in engineering.
• 10 years of experience in storage systems.
• 10 years of experience leading technical vision and strategy, including analyzing product positioning in the company and market.

Preferred qualifications:

• Experience building a storage system engine for a SQL relational database management system (RDBMS) or data warehouse.
• Experience building transaction processing systems (OLTP) or larger scale analytics (OLAP).
• Experience with and deep knowledge of open data formats (e.g. Apache Iceberg and Apache Parquet).
• Experience with high-availability designs, and parallel/horizontal scale-out database architectures.
• Excellent understanding of enterprise workloads, and a passion for delighting enterprise customers.
• Ability to think in a strategic manner to develop innovative product solutions, with a global mindset, and ability to operate effectively across geographic boundaries.

BigQuery is Google's serverless data warehousing and analytics system for the world's largest and most critical workloads. BigQuery pioneered the model of infinitely scalable, disaggregated storage among cloud data warehouses, and continues to innovate to bring insights to massive datasets as fast as possible.

Here in the BigQuery Storage team, we're continuing to innovate across the stack to bring a rich set of features into BigQuery, and inventing new ways to support workloads beyond traditional data warehousing to data lakes, Apache Iceberg support with the largest scale and lowest latency possible to meet the most demanding customer scenarios.

In this role, you will contribute to storage and data lakes in BigQuery. Storage in BigQuery encompasses the broad gamut of scenarios involving storage tiering, caching, encoding, ingestion/compaction, partitioning, data lakes, and Apache Iceberg formats. You'll use your knowledge of current and emerging storage and data lake technologies to help align our internal development with trends in the broader cloud ecosystem.

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 $278,000-$399,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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.

• Drive innovation across the BigQuery storage stack and beyond, maximizing execution bandwidth through thoughtful delegation and growth of future leaders.
• Oversee and steer storage engineering projects in multiple locations as well as drive cross-functional engineering decisions across the BigQuery sites to deliver exceptional storage and data lakes in BigQuery.  
• Provide domain expertise and engineering insight to guide early designs, accelerate project decision making, and maintain close oversight of technical execution, proactively adjusting course where necessary.
• Partner with engineering and product management teams to drive product direction. Travel to work with engineering teams and broader leadership both within BigQuery and broadly across Google.