Jobs
Benefits & Perks
•Team events and activities
•Comprehensive health, dental, and vision insurance
•Generous paid time off and holidays
•401(k) matching
•Parental leave
•Competitive salary and equity package
•Healthcare
•Parental Leave
•Equity
Required Skills
PostgreSQL
Node.js
React
P-1110
At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.
We are the “Spark™ Structured Streaming” team responsible for building Stream Processing capabilities into Spark™ and Databricks Intelligence Platform. Stream processing is in its infancy and we are here to build not just state of the art Stream Processing technology but best in class managed offering for customers to run their Stream Processing workloads.
We're seeking a dedicated Engineering Leader to spearhead Spark™ Structured Streaming development initiatives, encompassing both open source and Databricks-specific components. Your primary mission will be to make Spark™ Structured Streaming state of the art Stream Processing engine, by adding advanced features such as sophisticated state management, new operators and at the same time making the engine performance both from latency and throughput point of view by reimagining engine architecture.
The key responsibilities include:
Leading a talented engineering team in Spark™ Structured Streaming team developing and promoting the engine in OSS and the Databricks Data Intelligence Platform
Overseeing sustained recruitment of top-tier talent, and upskilling talent on the team
Implementing robust processes to efficiently execute product vision, strategy, and roadmap in alignment with organizational goals and priorities
Build software that is not just high quality but easy to operate.
Make company wide impact by driving Stream Processing adoption across the Databricks product portfolio
Manage technical debt, including long term technical architecture decisions and balance product roadmap
What we look for:
5+ years experience working in a related system, including big-data ecosystem, Apache Spark™ or database internal
A passion for database systems, storage systems, distributed systems, language design, or performance optimization
Can ensure the team builds high quality and reliable infrastructure services. Experience being responsible for testing, quality, and SLAs of a product. Previous experience building and leading teams in a complex technical domain, such as on distributed data systems or database internals
Ability to attract, hire, and coach engineers who meet the Databricks hiring standards. Can up level existing team via hiring top-notch senior talent, growing leaders and helping struggling members. Can gain trust of the team and guide their careers. Experience managing distributed teams preferred
Comfortable working cross functionally with product management and directly with customers; ability to deeply understand product and customer personas
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**$181,000**—$253,750 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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