Databricks developer

Architect and implement enterprise-grade Lakehouse solutions using Databricks.Design and deliver end-to-end data engineering pipelines, including batch and real-time streaming solutions.Lead implementation of:Cloud-based data lakehouse platforms integrating diverse data sources.Real-time data processing pipelines for operational and analytical use cases.Develop scalable ETL/ELT pipelines using PySpark, Scala, and SQL.Implement advanced data modeling solutions including 3NF, dimensional modeling, and enterprise data warehousing strategies.Design and build incremental data loading frameworks and metadata-driven ingestion pipelines.Establish data quality frameworks and governance standards.Implement and manage Unity Catalog, including fine-grained security and access controls.Leverage Databricks components such as:Delta Live TablesAutoloaderStructured StreamingDatabricks WorkflowsIntegration with orchestration tools (e.g., Apache Airflow)Drive CI/CD automation, deployment strategies, and DevOps best practices.Optimize performance of pipelines, Spark jobs, and compute resources.Provide architectural guidance and technical leadership across cross-functional teams.Engage with stakeholders and clients to translate business requirements into scalable technical solutions.Deep expertise in:Databricks and cloud-native storage/compute platformsApache Spark (batch & streaming)Delta Lake & Lakehouse architectureDistributed data processing systemsStrong hands-on programming skills in Python, PySpark, Scala, and SQL.