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Sr. Manager, Field Engineering - Emerging Enterprise

Databricks

Sr. Manager, Field Engineering - Emerging Enterprise

Databricks

United States

·

On-site

·

Full-time

·

3w ago

필수 스킬

Machine Learning

FEQ227R245

This Sr. Field Engineering Manager will lead a team of Solutions Architects (SA) focusing on clients in the Financial Services industry within our mid market segment (Emerging Enterprise).

This role will expand and develop a dynamic team skilled in working with customers to help them define their Data and AI strategy along with transforming their data engineering, analytics, and ML/AI workloads. It will require experience partnering with the sales organization to help grow consumption and win new workloads by enhancing your team's effectiveness; being an expert at communicating complex value-focused solutions; and building relationships with key stakeholders in large customers.

The impact you will have:

  • Hire, train, and grow a team of Solutions Architects for a company and business unit in high-growth mode.

  • Consistently meets or exceeds field targets by making sure the SA team knows how to qualify workloads - especially from a technical perspective, identify important use cases, build proof of concepts, and establish themselves as trusted advisors throughout the customer life-cycle.

  • Ensure customer success with Databricks and provide outsized value to their businesses.

  • Establish relationships across internal organizations (partners, services, sales, product, engineering, etc.) to ensure the success of the customers and team.

What we look for:

  • 5+ years of experience in the data space with a technical product (i.e. data warehousing, big data, cloud infrastructure, or machine learning).

  • 2+ years of experience building and leading technical customer-facing teams - hiring, onboarding, and supporting team members in a hypergrowth environment;

  • Experience in Financial Services industry as an IC or leader is a big plus

  • A history of building a territory; growing strategic accounts; and exceeding targets

  • Led a team through best practices for technical account strategy, architecture discussions, and solution advocacy in a highly competitive and political customer environment.

  • Inspiring a team vision about the unique nature of their group - to help foster a healthy and productive working relationship within the team and other organizations.

  • A history of execution by managing workloads and consumption with sales counterparts. Sharing learnings and blockers with the team and working to accelerate growth and adoption.

  • Experience with driving executive alignment in accounts that guide strategic data infrastructure decisions and establish partnerships through adoptions and growth.

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

Zone 1 Pay Range**$192,100—$264,175 USD**

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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Databricks 소개

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+

직원 수

San Francisco

본사 위치

$43B

기업 가치

리뷰

3.8

10개 리뷰

워라밸

2.8

보상

4.0

문화

4.2

커리어

3.5

경영진

4.0

72%

친구에게 추천

장점

Innovative technology and cutting-edge projects

Supportive and collaborative team environment

Good benefits and competitive compensation

단점

Poor work-life balance and long hours

High pressure and stressful environment

Heavy workload and overtime requirements

연봉 정보

34개 데이터

Mid/L4

Senior/L5

Mid/L4 · Corporate Development Manager

1개 리포트

$171,004

총 연봉

기본급

$148,699

주식

-

보너스

-

$171,004

$171,004

면접 경험

6개 면접

난이도

3.2

/ 5

소요 기간

21-35주

경험

긍정 0%

보통 83%

부정 17%

면접 과정

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Coding Round

5

Onsite/Virtual Interviews

6

Offer

자주 나오는 질문

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge