Jobs

Engineering Manager - Pipelines Engine
Mountain View, California; San Francisco, California
·
On-site
·
Full-time
·
1mo ago
Required skills
Spark
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 Lakeflow Engineering team, responsible for Databricks ETL product line: Jobs, Spark Declarative Pipelines, and Genie Code for Data Engineering. We run one of the world's biggest (if not the biggest) data engineering platforms - responsible for processing exabytes of data daily for tens of thousands of customers.
We're seeking a dedicated Engineering Leader to spearhead the Pipelines Engine engineering team. The team is responsible for building next generation Runtime ETL features and ensuring that Lakeflow Pipelines has state of art performance for ETL workloads. You will also spearhead the Agentic Data Engineering infrastructure, by building the next generation engine to power agentic pipeline authoring, execution and maintenance.
The main responsibilities include:
You will lead an engineering team building the next-generation ETL features for the Databricks Lakeflow platform.
You will oversee sustained recruitment of top-tier talent, and upskilling talent on the team.
You will build processes to implement product vision and strategy, according to organizational goals and priorities.
You will build software that is not just high quality but easy to operate.
You will manage technical debt, including long-term technical architecture decisions and balance product roadmap.
What we look for:
Minimum 3 years of experience in managing top-tier engineering teams
5+ years experience building data infrastructure systems such as Apache Spark™ or database internals.
A passion for database systems, storage systems, distributed systems, or performance optimization
Experience working with product management, and directly with customers; ability to understand customer needs.
Can ensure the team builds high quality and reliable infrastructure services. Experience being responsible for testing, quality, and Service Level Agreements of a product. Experience building and managing teams in a complex technical domain, such as on distributed data systems or database internals.
Expertise in attracting, hiring and coaching engineers, who will meet the Databricks hiring standards. Experience up-leveling teams via hiring top-notch talent and growing existing team members.
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**$190,000—$261,250 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
3.8
10 reviews
Work-life balance
2.8
Compensation
4.0
Culture
4.2
Career
3.5
Management
4.0
72%
Recommend to a friend
Pros
Innovative technology and cutting-edge projects
Supportive and collaborative team environment
Good benefits and competitive compensation
Cons
Poor work-life balance and long hours
High pressure and stressful environment
Heavy workload and overtime requirements
Salary Ranges
34 data points
Mid/L4
Senior/L5
Mid/L4 · Corporate Development Manager
1 reports
$171,004
total per year
Base
$148,699
Stock
-
Bonus
-
$171,004
$171,004
Interview experience
6 interviews
Difficulty
3.2
/ 5
Duration
21-35 weeks
Experience
Positive 0%
Neutral 83%
Negative 17%
Interview process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Coding Round
5
Onsite/Virtual Interviews
6
Offer
Common questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
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