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Customer Engineering Manager, Data Analytics, Google Cloud

Google

Customer Engineering Manager, Data Analytics, Google Cloud

Google

placeNew York, NY, USA; Cambridge, MA, USA; +2 more; +1 more

·

On-site

·

Full-time

·

1mo ago

Compensation

$186,000 - $261,000

Benefits & Perks

Team events and activities

Professional development budget

Generous paid time off and holidays

Flexible work arrangements

Comprehensive health, dental, and vision insurance

Competitive salary and equity package

Learning

Flexible Hours

Healthcare

Equity

Required Skills

React

TypeScript

PostgreSQL

About the job

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 Customer Engineering (CE) Manager, you will lead and deploy a team of subject matter experts responsible for working alongside our customers to provide trusted technical and solution advice to accelerate workload migration and remove technical impediments.

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 $186,000-$261,000 + 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

  • Lead a team of technical experts in an organization. Focus on talent strategy, assessing go-to-market readiness and gaps in CE preparedness, skills development, and opportunity coverage to deliver successful cloud transformation outcomes for customers and accelerate business goals.

  • Execute the technical goal and strategy for region’s Data Analytics practice. Lead the broader region's Data Analytics technical community, to ensure sub-regional technical contributions, achieve scale through artifact and innovation sharing.

  • Influence cross-functional teams, including product management and engineering, ensuring customer needs are represented in product roadmaps and new technology is incubated and scaled.

  • Lead technical engagements with strategic customers, working with cross-functional peers to plan customer engagements.

  • Travel up to 25% to customer sites, conferences, and other related events as required, acting as a public advocate for Google Cloud.

Minimum qualifications

  • Bachelor's degree or equivalent practical experience.

  • 10 years of experience with cloud native architecture in a customer-facing or support role.

  • Experience with Data Analytics technologies or concepts, cloud, and on-premise technologies.

  • Experience in pre-sales or field engineering at an enterprise technology company, or customer facing.

  • Experience in pre-sales management, people management on a data analytics-related or technical team.

  • Experience engaging with, and presenting to, technical stakeholders and executive leaders.

Preferred qualifications

  • Experience in thought leader in Data Analytics and adjacent practice areas, specialized in technical sales and strategizing around holistic customer and industry solutions.

  • Experience influencing cross-functional teams (e.g., product management, engineering, sales), customers, and partners to impact business goals, customer experience, and customer expansion.

  • Experience in big data including analytics warehousing, data processing, data transformation, data governance, data migrations, ETL, ELT, SQL, NoSQL, performance or scalability optimizations.

  • Experience tailoring and delivering compelling messages by the audience, asking strategic questions, and leading conversations that drive business opportunities.

  • Experience in, or supporting, industries (e.g., financial services, retail or geos).

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About Google

Google

Google

Public

Google specializes in internet-related services and products, including search, advertising, and software.

10,001+

Employees

Mountain View

Headquarters

$1,700B

Valuation

Reviews

3.7

25 reviews

Work Life Balance

3.8

Compensation

4.2

Culture

3.4

Career

3.9

Management

2.8

68%

Recommend to a Friend

Pros

Excellent compensation and benefits

Smart and talented colleagues

Great perks and work flexibility

Cons

Management and leadership issues

Bureaucracy and slow processes

Constantly changing priorities and reorganizations

Salary Ranges

63,375 data points

Junior/L3

L3

L4

L5

L6

L7

L8

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L3

0 reports

$176,704

total / year

Base

-

Stock

-

Bonus

-

$150,298

$203,110

Interview Experience

9 interviews

Difficulty

3.4

/ 5

Duration

14-28 weeks

Offer Rate

44%

Experience

Positive 0%

Neutral 56%

Negative 44%

Interview Process

1

Application Review

2

Online Assessment/Technical Screen

3

Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Product Sense