
Data Engineering Specialist
2 weeks ago
A dynamic Databricks administrator is required to lead our data engineering efforts. This pivotal role demands a deep understanding of Databricks administration, combined with experience in AWS infrastructure and data warehousing concepts.
Key Responsibilities- Databricks Cluster Management: Oversee the management and optimization of Databricks clusters at scale, ensuring high availability and performance.
- Deployment & Configuration: Manage deployments within Databricks, utilizing System tables for monitoring and management.
- Troubleshooting & Support: Provide expert troubleshooting capabilities for issues within Databricks notebooks and address Databricks-related queries from the community.
- Cloud & Data Platform Fundamentals: Leverage knowledge of AWS services and strong fundamentals of Data Warehousing (DW) / Data Lakehouse (DH) concepts.
- Coding & Automation: Utilize Spark/Python for scripting and automation within the Databricks environment.
- Containerization & Orchestration: Work with Docker and Kubernetes.
- AWS Services Integration: Harness expertise in relevant AWS services such as S3, Lambda, and EMR.
- Deep understanding of AWS, Databricks, and Unity Catalog.
- Proven experience in managing Databricks clusters and deployments.
- Strong fundamentals of Data Warehousing (DW) / Data Lakehouse (DH) concepts.
- Expert troubleshooting abilities within the Databricks environment.
- Proficiency in Spark/Python.
- Experience with Docker, Kubernetes, and AWS services (S3, Lambda, EMR).
- Expertise in managing clusters at scale and troubleshooting within Databricks.
- Experience working with Databricks System tables.
- Strong knowledge of Databricks infrastructure and administration.
- Bachelor's degree in Computer Science, Engineering, or a related field.
- Typically seeking candidates with 6+ years of relevant experience.
- Certified Databricks Engineer is required.
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