Senior Software Engineer - Database Engine Internals

Databricks
Mountain View, CA, United States
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$166,000.0 - $225,000.0
Working hours
Regular working hours

Tech stack

Query Performance Artificial Intelligence Encodings Cyber Security Databases Extract Transform Load (ETL) Data Security Data Warehousing Distributed Systems Performance Tuning Query Optimization Software Engineering
+3 more
Database Engines Apache Spark Databricks

Job description

Our mission at Databricks is to radically simplify the whole data lifecycle from ingestion to ETL, BI, and all the way up to ML/AI with a unified platform. To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse (CIDR 2021 paper), open platforms that unify data warehousing and advanced analytics. The new architecture will help address several major challenges, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support.

A critical part of realizing this vision is the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance, yet retain the expressiveness and of general purpose systems such as Apache Spark to support diverse workloads ranging from ETL to data science.

As part of this team, you will be working in one or more of the following areas to design and implement these next gen systems that leapfrog state-of-the-art:

  • Query compilation and optimization
  • Distributed query execution and scheduling
  • Vectorized execution engine
  • Data security
  • Resource management
  • Transaction coordination
  • Efficient storage structures (encodings, indexes)
  • Automatic physical data optimization

Requirements

Software Engineering, Total Cost of Ownership, Architectural Services, Use Cases, Data Warehousing, Database Extract Transform and Load (ETL), Data Science, Apache Spark, Query Optimization, Information/Data Security (InfoSec), * A passion for database systems, storage systems, distributed systems, language design, or performance optimization

  • Experience working towards a multi-year vision with incremental deliverables
  • Motivated by delivering customer value and impact
  • 5+ years of experience working in a related system (preferred)
  • Optional: PhD in databases or distributed systems

Pay Range Transparency

Benefits & conditions

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 $166,000-$225,000 USD, 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 click here.

About the company

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide - including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 - rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

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