Job Description: Senior Databrick EngineerResponsibilities:Develop and optimize ETL pipelines from various data sources using Databricks on cloud (AWS, Azure, etc.)Experienced in implementing standardized pipelines with automated testing, Airflow scheduling, Azure DevOps for CI/CD, Terraform for infrastructure as code, and Splunk for monitoringContinuously improve systems through performance enhancements and cost reductions in compute and storageData Processing and API Integration: Utilize Spark Structured Streaming for real-time data processing and integrate data outputs with REST APIsLead Data Engineering Projects to manage and implement data-driven communication systemsExperienced with Scrum and Agile Methodologies to coordinate global delivery teams, run scrum ceremonies, manage backlog items, and handle escalationsIntegrate data across different systems and platformsStrong verbal and written communication skills to manage client discussions.Candidate Profile:8 years experience in developing and implementing ETL pipelines from various data sources using Databricks on cloudBased out of USSome experience in insurance domain/ data is mustProgramming Languages – SQL, PythonTechnologies - IaaS (AWS or Azure or GCP), Databricks platform, Delta Lake storage, Spark (PySpark, Spark SQL).Good to have - Airflow, Splunk, Kubernetes, Power BI, Git, Azure Devops