
Data Engineering Leader
2 weeks ago
We are seeking an expert Data Engineering leader to manage and maintain our Databricks infrastructure. The successful candidate will have extensive experience in managing large-scale distributed systems, implementing automation scripts using Python and Spark, and providing exceptional support to our analyst community.
About the Role- Key Responsibilities:
- Manage and optimize Databricks clusters at scale, ensuring high availability and performance.
- Oversee deployments within Databricks and work with Databricks System tables for monitoring and management.
- Provide strong troubleshooting capabilities for issues within Databricks notebooks and address Databricks-related queries from the analyst community.
- Apply good knowledge of AWS services and strong fundamentals of Data Warehousing (DW) / Data Lakehouse (DH) concepts.
- Utilize Spark/Python for scripting and automation within the Databricks environment.
- Work with Docker and Kubernetes.
- Leverage knowledge of relevant AWS services such as S3, Lambda, and EMR.
- Good knowledge of AWS, Databricks, and Unity Catalog.
- Strong experience in managing Databricks clusters and deployments.
- Strong fundamentals of Data Warehousing (DW) / Data Lakehouse (DH) concepts.
- Strong troubleshooting abilities within the Databricks environment.
- Proficiency in Spark/Python (either coding skills).
- 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 to support the Analyst community in addressing Databricks-related queries and troubleshooting issues in notebooks.
- Bachelor's degree in Computer Science, Engineering, or a related field.
- Proven experience as a Databricks Admin or in a similar role.
- Typically seeking candidates with 6+ years of relevant experience.
- Certified Databricks Engineer is required.
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