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Enterprise Sales Account Executive - Professional Services

Databricks

Enterprise Sales Account Executive - Professional Services

Databricks

London, United Kingdom

·

On-site

·

Full-time

·

2w ago

Required Skills

Enterprise software sales

Executive relationship management

New business development

SaaS sales

Account planning

MEDDPICC

Challenger Sales

Command of the Message

SLSQ427R120

Want to help solve the world's toughest problems with big data and AI? This is what we do every day at Databricks.

As an Enterprise Account Executive, you will come with an informed and compelling point of view on the Big Data, Advanced Analytics, and AI space which will guide your successful strategy and together with both our teams and partners, allow you to provide exceptional value to our customers within the Professional Services sector. Reporting to the Sales Director, you will be focused on the growth of professional service accounts.

The impact you will have:

  • You will provide the industry insight and business creativity required to design and develop unique use cases and solutions that differentiate Databricks within the PBS segment.

  • You will co-develop a business plan, with your team and ecosystem partners, that accelerates existing customer success, identifies and acquires new opportunity and enables you to exceed quarterly/annual usage and booking goals

  • You will motivate a diverse team of big data and AI professionals to implement your business plan

  • You will lead your team, customers, and partners to identify impactful big data and AI use cases whilst proving their value on the Databricks Data Intelligence Platform

  • You will support the broader big data and AI transformation goals of your customers through a combination of strategic partnerships, well-scoped professional services, training, and targeted Executive engagement

  • You will build exceptional value with all engagements to guide successful negotiations to close

What we look for:

  • Experience in direct sales of enterprise software platforms to large enterprises

  • Ownership of executive level relationships in your clients

  • Proven track record of developing new business

  • Extensive experience of working with large complex regulated organisations

  • Knowledge of the Data & AI space with technology sales experience

  • Longevity with previous employers

  • Quota over-achievement and significant growth when selling complex software and services to Enterprise accounts

  • Experience driving successful adoption of usage-based subscription services (SaaS) and co-selling with AWS, Azure and Google Cloud teams

  • Methods for co-developing business cases and gaining support from C-level Executives

  • Familiarity with sales methodologies and process (e.g Territory and Account planning, MEDDPICC, Challenger Sales and Command of the Message)

  • Experience developing partnerships with "champions" and client teams to support execution of your territory plan

  • Experience developing a clear partner strategy and implement it to achieve success

  • Understanding of consumption-based, land and expand sales models advantageous

  • Understanding of how to identify important uses cases and buying centres to increase the impact of Databricks for clients

About Databricks

Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.

Benefits:

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks.

Our Commitment to Diversity and Inclusion:

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

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About Databricks

Databricks

Databricks

Series I

Databricks, Inc. is an American software company based in San Francisco. It was founded in 2013 by the original creators of Apache Spark. It offers a cloud-based platform for data analytics and artificial intelligence.

6,000+

Employees

San Francisco

Headquarters

$43B

Valuation

Reviews

4.2

9 reviews

Work Life Balance

3.5

Compensation

4.7

Culture

4.3

Career

4.5

Management

4.0

86%

Recommend to a Friend

Pros

Working on industry-leading data and AI platform

Excellent compensation with high equity upside

Strong engineering culture with Apache Spark creators

Cons

High intensity work environment with demanding deadlines

Work-life balance can suffer during key releases

Growing pains as company scales rapidly

Salary Ranges

25 data points

Mid/L4

Senior/L5

Mid/L4 · Corporate Development Manager

1 reports

$171,004

total / year

Base

$148,699

Stock

-

Bonus

-

$171,004

$171,004

Interview Experience

9 interviews

Difficulty

3.0

/ 5

Duration

21-35 weeks

Offer Rate

22%

Experience

Positive 22%

Neutral 67%

Negative 11%

Interview Process

1

Application Review

2

Recruiter/Phone Screen

3

Technical Interview/Coding Round

4

System Design Interview

5

Behavioral Interview

6

Final Round/Hiring Manager Interview

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge