Leverage Databricks for tasks such as writing complex SQL queries, applying business logic, and utilizing big data best practices and can significantly enhance the efficiency and scalability of identifying and analyzing log data.
By taking advantage of Databricks' collaborative notebooks, integrated data lake, and optimized Apache Spark environment, you will need to be able to seamlessly categorize opportunities, analyze large volumes of data, and apply statistical methodologies and data mining skill sets.
Connecting Databricks with visualization tools like Tableau enables the creation of insightful dashboards.
Skills and Experience:
9 years of experience.
Skill set centered around Databricks, including proficiency in SQL for complex query writing, a deep understanding of Databricks' collaborative notebooks for applying business logic and conducting data analysis, expertise in Apache Spark for leveraging big data best practices, and familiarity with data integration techniques to connect Databricks with visualization tools like PowerBi or Graphana.
Additionally, skills in statistical methodologies, data mining, and machine learning within the Databricks environment are crucial for analyzing large data volumes and deriving insights.
Effective communication and the ability to present complex findings to other engineers.