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# Senior Software Engineer - Database Engine Internals

- **Company:** Databricks
- **Location:** Mountain View, CA, United States
- **Experience:** Expert
- **Salary:** $166,000.0 - $225,000.0
- **Contract:** Permanent contract
- **Skills:** Query Performance, Artificial Intelligence, Encodings, Cyber Security, Databases, Extract Transform Load (ETL), Data Security, Data Warehousing, Distributed Systems, Performance Tuning, Query Optimization, Software Engineering, Database Engines, Apache Spark, Databricks
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-software-engineer-database-engine-internals-mountain-view-ca--0eb91110-a25f-400a-81a0-e26ad5bb91fa

## About the Role

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

## 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