채용
Benefits & Perks
•Parental leave
•401(k) matching
•Professional development budget
•Generous paid time off and holidays
•Team events and activities
•Flexible work arrangements
•Parental Leave
•Learning
•Flexible Hours
Required Skills
Node.js
Python
PostgreSQL
As a Sr. Solutions Architect at Databricks within the Field Engineering org, you will partner with our customers to design scalable data architectures using Databricks technology and services. You have technical depth and business knowledge, and can drive complex technology discussions that express the value of the Databricks platform throughout the sales lifecycle. In partnership with our Account Executives, you will engage with our customers' technical leads, including architects, engineers, and operations teams, with the goal of establishing yourself as a trusted advisor to achieve tangible outcomes. You will work with teams across Databricks and our executive leadership to represent your customers' needs, build valuable customer engagements, and report to the Field Engineering Manager.
The impact you will have:
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You will work with Sales and other essential partners to develop account strategies for your assigned accounts to grow their usage of the platform.
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Establish the Databricks Lakehouse architecture as the standard data architecture for customers through excellent technical account planning.
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You will build and present reference architectures and demo applications for prospects to help them understand how Databricks can be used to achieve their goals to land new users and use cases.
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Capture the technical win by consulting on big data architectures, data engineering pipelines, and data science/machine learning projects; prove out the Databricks technology for strategic customer projects; and validate integrations with cloud services and other 3rd party applications.
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Become an expert in and promote Databricks-inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars.
What we look for:
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8+ years in a customer-facing pre-sales or consulting role with expertise in at least one of the following technologies:
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Big data engineering (Ex: Spark, Hadoop, Kafka)
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Data Warehousing & ETL (Ex: SQL, OLTP/OLAP/DSS)
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Data Science and Machine Learning (Ex: pandas, scikit-learn, HPO)
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Data Applications (Ex: Logs Analysis, Threat Detection, Real-time Systems Monitoring, Risk Analysis and more)
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Experience translating a customer's business needs to technology solutions, including establishing buy-in with essential customer stakeholders at all levels of the business.
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Experienced at designing, architecting, and presenting data systems for customers and managing the delivery of production solutions of those data architectures.
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Fluent in SQL and database technology.
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Debug and development experience in at least one of the following languages: Python, Scala, Java, or R.
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Desired Built solutions with public cloud providers such as AWS, Azure, or GCP
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Desired Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
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Travel to customers in your region up to 30% of the time.
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.
Local Pay Range:
$196,200—$274,650 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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About Databricks

Databricks
Series IDatabricks, 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
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