Customer Engineer II, Data Analytics, Cloud

This role may also be located in our Playa Vista, CA campus.

Applicants in the County of Los Angeles:
Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Applicants in San Francisco:
Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.

The application window will be open until at least February 18, 2026. This opportunity will remain online based on business needs which may be before or after the specified date.

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:

• 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 (statutory, where applicable); 5 days/event (discretionary)
• Maternity Leave (Short‑Term Disability + Baby Bonding): 28‑30 weeks
• Baby Bonding Leave: 18 weeks
• Holidays: 13 paid days per year

Note:

By applying to this position you will have an opportunity to share your preferred working location from the following:
Sunnyvale, CA, USA;
Boulder, CO, USA;
Irvine, CA, USA;
Phoenix, AZ, USA;
Los Angeles, CA, USA;
San Diego, CA, USA;
Seattle, WA, USA;
San Francisco, CA, USA;
Salt Lake City, UT, USA
.

• Bachelor's degree or equivalent practical experience.
• 6 years of experience with cloud native architecture in a customer-facing or support role.
• Experience engaging with, or presenting to, technical stakeholders or executive leaders.
• Experience with Big Data technologies or concepts (e.g., analytics warehousing, data processing, data transformation, data governance, data migrations, ETL, ELT, SQL, Spark, performance or scalability optimizations, batch versus streaming).
• Experience using programming languages (e.g., Python, Spark, SQL) to demo, prototype, or workshop with customers.

• Experience in technical sales or consulting in cloud computing, data analytics, and Big Data.
• Experience with developing data warehousing, data lakes, batch/real‑time event processing, streaming, data processing (ETL/ELT), data migrations, data visualization tools, and data governance on cloud native architectures.
• Experience with architecture design, implementing, tuning, schema design, and query optimization of scalable and distributed systems.
• Experience with cloud computing (e.g., infrastructure, storage, platforms, data) and the cloud market, participant dynamics, and customer buying behavior.
• Experience understanding customer requirements with the ability to break down requirements and design technical architectures.

When leading companies choose Google Cloud, it’s a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem‑solving key technical issues for our customers.

You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products.

As a Practice Customer Engineer (CE) with a specialty in Data Analytics, you will partner with technical sales teams to differentiate Google Cloud to our customers. You will serve as a technical expert responsible for accelerating technical wins and adoption of complex, specialized workloads. You will leverage your deep expertise in our most strategic product areas, in partnership with Platform CEs, to design data foundation architectures and develop MVPs (Minimum Viable Products) to promote new, highly specialized solutions to…