P-961

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. This new architecture will help address several major challenges, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support.

To achieve this vision, Databricks is building the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance. Yet we will retain the expressiveness and robustness of general purpose systems such as Spark to support diverse workloads ranging from ETL to data science. You will be part of this multi-year journey.

As part of this team, you will design these next-generation systems that leapfrog state-of-the-art within the following areas:

• 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

The responsibilities you will have:

• Drive requirements clarity and design decisions for ambiguous problems
• Produce technical design documents and project plans
• Develop new features
• Mentor more junior engineers
• Test and rollout to production, monitoring.

What we look for:

• A passion for database systems, storage systems, distributed systems, language design, or performance optimization
• Are comfortable working towards a multi-year vision with incremental deliverables
• Be customer-oriented and focused on having an impact
• 7+ years of experience working in a related system
• Optional: PhD in databases or distributed systems