Need Advice on Preparing for Google US Data Engineering Intern Interview!

I recently received an interview invitation for the Data Engineer Summer Internship at Google US, and I’m feeling a bit overwhelmed with how to best prepare. I’m confused about what topics to focus on, what types of problems to expect, and any general tips for tackling the interview process. Has anyone been through this interview before, or does anyone have guidance on study materials, preparation strategies, or any insider insights on the process?
For context, here’s the finish job description I received:
By applying to this position, your application will be considered for all Data Engineer roles at all locations we bring on for in the United States including but not limited to: Greater Seattle Area (Seattle, Bellevue, Redmond), Greater Bay Area (San Francisco, Sunnyvale, Santa Clara), Greater DMV (DC, MD, VA), Austin (TX), New York City (NY), Minneapolis (MN).
You will be capable to provide your preference of location and start date during the application process but, we cannot guarantee that we can meet your selection based on several factors including but not limited to the availability and business needs of this role. Finalization on the location and start dates available will be provided to you at the time of gig offer.
Start dates for our internships in this posting include the following period:
Summer (Starts May/June 2027)
Do you love building data pipelines? Are you excited by the opportunity to design tools and infrastructure needed to analyze large volumes of data? Do you want to help solve big data warehousing problems, and partner with stakeholders to understand how to best design and implement cutting edge data solutions that provide answers to key business problems? Do you hope to be a part of a fast-paced environment and contribute to one of the most visited sites on the Internet?
If this describes you, consider joining us as an Google is looking for a data engineer intern to join one our plenty of lines of business. Google interns have the opportunity to gig alongside the industry’s brightest engineers who innovate every day on behalf of our customers. You will be matched to a manager and a mentor. You will have the opportunity to impact the evolution of Google technology as well as lead mission critical projects early in your career. Your work will contribute to solving some of the most complex technical challenges in the shop.
Please review the following page for information on Google University Talent's recruiting timeline and additional FAQs: https://techengamazon.splashthat.com/.
Key gig responsibilities
As a Data Engineer intern, you will/may:
Design, implement, and automate deployment of our distributed system for collecting and processing log events from multiple sources.
Design data schema and operate internal data warehouses and SQL/NoSQL database systems.
Own the design, development, and maintenance of ongoing metrics, reports, analyses, and dashboards that engineers, analysts, and data scientists use to drive key business decisions.
Monitor and troubleshoot operational or data issues in the data pipelines.
Analytic solutions, and Drive architectural plans and implementation for future data storage, reporting.
Develop code based automated data pipelines capable to process millions of data points.
Improve database and data warehouse performance by tuning inefficient queries.
Work collaboratively with Business Analysts, Data Scientists, and other internal partners to identify opportunities/problems.
Provide assistance with troubleshooting, researching the root cause, and thoroughly resolving defects in the event of a problem.
A day in the life
In addition to employed on an impactful project, you will have the opportunity to engage with Amazonians for both personal and professional development, expand your network, and participate in fun activities with other interns throughout the summer. No matter the location of your internship, we give you the tools to own your summer and learn in a real-world setting.
We’re on the lookout for the curious, those who suspect big and want to define the world of tomorrow.
At Google, you will grow into the high impact, visionary person you understand you’re ready to be. Achieving personal growth, and Every day will be filled with exciting fresh challenges, developing new skills.
How often can you say that your gig changes the world? At Google, you’ll say it frequently. Join us and define tomorrow.
Basic Qualifications
Experience with database, data warehouse or data lake solutions
Experience with SQL
Experience with one or more scripting language (e.g., Python, KornShell, Scala)
Are 18 years of age or older
Work 40 hours/week minimum and commit to 12 week internship maximum
Experience with data transformation.
Currently enrolled in or will receive a Bachelor’s in Computer Science, Computer Engineering, Information Management, Information Systems, or an equivalent technical discipline with a conferral date between October 2026 – December 2029.
Preferred Qualifications
Knowledge of basics of designing and implementing a data schema like normalization, relational model vs dimensional model
Experience building data pipelines or automated ETL processes
Experience writing and optimizing SQL queries with large-scale, complex datasets
Experience with large data processing technology (e.g., Hadoop or ApacheSpark), data warehouse technical architecture, infrastructure components, ETL, and reporting/analytic tools and environments
Experience with data visualization software (e.g., AWS QuickSight or Tableau) or available-source project
Enrolled in a Master’s Degree or advanced technical degree with a conferral date between October 2026 – December 2029.
Previous technical internship(s), if applicable
Prior background with AWS
Can articulate the basic differences between datatypes (e.g. JSON/NoSQL, relational)
Given the extensive nature of the job and responsibilities, I’m unsure where to begin. Should I focus more on building data pipelines, brushing up on SQL and database design, or dive deeper into large data processing frameworks like Apache Spark? Also, if anyone has specific tips for interviews at Google, especially for Seattle-based roles, please share your insights and any resources that might have helped you.
Thanks in advance for your aid!
Looking forward to your guidance and experiences.