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Software Engineer - DLT PhD Candidates

Databricks

Software Engineer - DLT PhD Candidates

Databricks

Mountain View, California

·

On-site

·

Full-time

·

1mo ago

Compensation

$150,000 - $190,000

Benefits & Perks

Team events and activities

Professional development budget

Flexible work arrangements

401(k) matching

Learning

Flexible Hours

Required Skills

JavaScript

TypeScript

Node.js

P-187

Databricks is radically simplifying the entire data lifecycle, from ingestion to generative AI and everything in-between. We’re doing it cross-cloud with a unified platform, serving over 10k customers, processing exabytes of data/day on 15+ million VMs, and growing exponentially.

The Delta Live Tables team (DLT) is looking for recent PhD graduates. Delta Live Tables (DLT) makes it easy to build and manage reliable batch and streaming data pipelines that deliver high-quality data on the Databricks Lakehouse Platform. DLT helps data engineering teams simplify ETL (extract-transform-load) development and management with declarative pipeline development, automatic data testing, and deep visibility for monitoring and recovery. DLT optimizes pipeline execution by logical optimization through query transformations, and physical optimization such as instance type selection and vertical/horizontal autoscaling.

Moreover, as part of DLT, we have a new catalyst optimization layer, enzyme, designed specifically to speed up the ETL process and make declarative ETL computation possible by incrementally computing and materializing the intermediate results. Enzyme can create and keep up-to-date a materialization of the results of a given query stored in a Delta table. Enzyme does this by using a cost model to choose between a variety of techniques that borrow from traditional literature on the maintenance of materialized views, delta-to-delta streaming, and manual ETL patterns commonly used by our customers.

As a part of the DLT team, there are opportunities to design and implement in many areas that leapfrog existing systems:

  • Query compilation and optimization

  • Distributed query execution and scheduling

  • Vectorized engine execution

  • Resource Management

  • Transaction coordination

  • Efficient storage structures (encoding, indexes)

  • Automatic physical data optimization

What We Look For:

  • PhD in databases or systems

  • Knowledge of database systems, storage systems, distributed systems, and performance optimization

  • Motivated by delivering customer value and influence

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:

$150,000—$190,000 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

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