We are seeking a skilled Databricks Architect to design, implement, and optimize scalable data solutions within our cloud-based data platform. This role requires extensive knowledge of Databricks (Azure/AWS), data engineering, and a deep understanding of data architecture principles, with the ability to drive strategy, best practices, and hands-on implementation for high-performance data processing and analytics solutions.
Responsibilities:
- Solution Architecture:
- Design and architect end-to-end data solutions using Databricks and Azure/AWS, including data ingestion, processing, and storage.
- Delta Lake Implementation:
- Leverage Delta Lake and Lakehouse architecture to create robust, unified data structures that support advanced analytics and machine learning.
- Data Processing Development:
- Develop, design, and automate large-scale, high-performance data processing systems (batch and/or streaming) to drive business growth and enhance the product experience.
- Performance Tuning:
- Ensure optimal performance of data pipelines and workloads by implementing best practices for resource management, auto-scaling, and query optimization in Databricks.
- Engineering Best Practices:
- Advocate for high-quality software engineering practices in building scalable data infrastructure and pipelines.
- Architecture/Solution Development:
- Develop Architecture or solution for large data project using Databricks.
- Project Leadership:
- Lead data engineering projects to ensure pipelines are reliable, effective, testable, and maintainable.
- Data Modeling:
- Design data models optimized for storage, retrieval, and critical product and business requirements.
- Logging Architecture:
- Understand and influence logging to support data flow, implementing logging best practices as needed.
- Standardization and Tooling:
- Contribute to shared data engineering tools and standards to boost productivity and quality for Data Engineers across the company.
- Collaboration:
- Work closely