Director of Engineering (Data Infrastructure)
Databricks · Bangalore, India · Executive Engineering - Pipeline
About this role
Databricks is hiring a vp-level VP of Engineering in the software engineering function based in Bangalore, India. The posting calls out experience with Kafka, Spark, Databricks, MLflow.
- Role
- VP of Engineering
- Function
- software engineering
- Level
- vp
- Track
- Management
- Employment
- Full-time
- Location
- Bangalore, India
- Department
- Executive Engineering - Pipeline
More roles at Databricks
Job description
from Databricks careers(P-1490)
Databricks processes petabytes of data and billions of transaction events daily - every cluster launch, every query executed, every dollar billed flows through infrastructure that must never fail. When we process billions in billing transactions with 99.999% accuracy requirements, when we ingest terabytes per second across 100+ regions, when a five-minute outage costs millions in revenue and customer trust - infrastructure isn't just important, it's existential. The next phase of our growth demands disaster recovery systems that prove reliability rather than hope for it, testing frameworks that catch production-scale problems before deployment, correctness guarantees that make billing errors structurally impossible, and automation that scales operations sublinearly with growth.
In this leadership opportunity, you will build the data infrastructure organization that makes Databricks' continued growth possible. You'll establish foundational teams in Bengaluru owning the bedrock systems that guarantee billing correctness, operational resilience, and zero-downtime recovery across our entire monetization stack, alongside multi-region data ingestion, developer platforms, and deployment automation that eliminate friction at petabyte scale. This isn't about maintaining what exists; it's about architecting the infrastructure that enables Databricks to scale while reducing operational burden. You'll define what world-class infrastructure looks like for the next decade of data platforms.