Senior Databricks Data Engineer
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ResponsibilitiesData Solution Design and DevelopmentDesign, develop, and implement complex, scalable Lakehouse solutions on the Databricks platform across major cloud environments (Azure, AWS, or GCP).Design, build, and optimize modular data pipelines using Delta Lake to ensure data efficiency, reliability, and quality.Implement data governance and secure data access layers utilizing Databricks Unity Catalog.Programming & ScriptingWrite clean, efficient, and maintainable SQL and Python code within Databricks Notebooks and IDEs.Develop automation scripts leveraging the Databricks CLI and REST APIs to manage workspace assets and configurations.DevOps & AutomationEstablish, maintain, and optimize CI/CD pipelines (e.g., GitHub Actions, GitLab CI/CD) leveraging Declarative Automation Bundles (DABs) as the primary mechanism for rapid, reliable, and software-defined project deployments.Automate and orchestrate data pipeline processes using Databricks Workflows or Spark Declarative Pipelines (formerly DLT) Cloud Data ServicesDeliver solutions centered on the Databricks ecosystem, integrating seamlessly with cloud-native storage and security services (e.g., AWS S3/IAM, Azure ADLS/Entra ID, or Google Cloud Storage/IAM).Design and implement modern data modeling and data warehousing solutions using Databricks SQL Warehouses.Project and Team ManagementOwn and manage the technical aspects of deliveries (at least at component level).Participate in project planning, task estimation, testing, and liaising with business stakeholders.Create comprehensive technical documentation.