Azure Databricks Architect
System Soft
San Francisco, CA, United States
about 2 months ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Working hours
Regular working hours
Job source
Tech stack
Amazon Web Services
Microsoft Azure
Continuous Integration
Information Engineering
Extract Transform Load (ETL)
Data Systems
Data Warehousing
DevOps
Memory Management
Github
Machine Learning
Performance Tuning
+12 more
Cloud Services
Data Streaming
Google Cloud
Apache Spark
Data Lakes
Gitlab-ci
Data Analytics
Data Management
Machine Learning Operations
Data Pipelines
Jenkins
Databricks
Requirements
- 12-15+ years of experience in Data Engineering, Data Platforms, Data Analytics, and Modern Data Warehouse solutions, with 10+ years of overall consulting and client-facing delivery experience.
- Demonstrated success delivering 6-8+ end-to-end Databricks implementations, serving as a hands-on developer, technical lead, or solution architect.
- Databricks Data Engineering Professional certification with completion of all recommended learning paths and coursework.
- Databricks has a Databricks Solutions Architect Champion program- this will be good to have
- Strong expertise in designing and implementing cloud-native data platforms across AWS, Azure, and/or Google Cloud Platform, with deep hands-on proficiency in at least one cloud ecosystem.
- Advanced knowledge of Apache Spark, including performance optimization, partitioning strategies, execution plans, memory management, and Spark runtime internals.
- Extensive hands-on experience developing scalable ETL/ELT pipelines using Databricks, Delta Lake, Structured Streaming, and modern data engineering frameworks.
- Experience implementing DevOps and CI/CD practices for production-grade data solutions using tools such as Azure DevOps, GitHub Actions, GitLab CI/CD, or Jenkins.
- Working knowledge of MLOps principles, machine learning lifecycle management, model deployment, and monitoring within enterprise environments.
- Current and broad understanding of the Databricks Lakehouse Platform, including Delta Lake, Unity Catalog, Workflows, MLflow, Delta Live Tables, and other platform capabilities.
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Prepare application
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