Databricks Lead

4 weeks ago


Chicago, United States eTeam Full time
Must Have
  • Bachelors degree in Computer Science, a related field, or applicable work experience.
  • 7+ years of overall IT experience with 5+ years of experience in Databricks platform development & administration, Spark and cloud experience in AWS, Azure or GCP cloud (GCP preferred).Primary skills: Databricks administration & development
  • Databricks Resource Management
Skills and Expertise
  • In-depth understanding of Big Data ecosystems underlying architectures to re-platform legacy systems and build integration solutions on Google Cloud platform.
  • Experience in design and development of machine learning pipelines to process structured and unstructured data streams.
  • Hands on experience developing complex services/solutions on Databricks Platform.
  • Expertise in Java, Python or any scripting language, SQL/NoSQL Database systems.
  • Experience in Big Data tools and technologies such as Big Query, Databricks, Snowflake, Spark, Kafka Streams
  • Have a passion for new technologies, continuous improvement and actively involved with the team to design new data solutions, monitoring and alerting policies for data solutions.
  • Experience in test automations ensuring data quality, continuous integrations build and deployment processes using Docker, GitHub, Jenkins and Unix/Linux shell scripts.
  • Design and implement frameworks and data pipelines for large-scale data processing on Databricks that will power data science capabilities across the enterprise.
  • Develop MLOps frameworks which will enable model development, training, deployment, and monitoring.
  • Configure and manage Databricks clusters ensuring optimal performance, scalability, and resource utilization.
  • Manages user provisioning and access controls within the Databricks environment.
  • Monitor cluster health, performance metrics, and resource consumption. Scale clusters based on workload demands.
  • Troubleshoot and resolve issues related to connectivity, and performance bottlenecks.
  • Manage Databricks workspaces, including creating notebooks, folders, and organizing resources for different teams and projects


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