• Collaborate with team members and stakeholders to understand data requirements and contribute to building scalable data pipelines and workflows in Databricks. • Develop and implement ETL/ELT processes using Databricks, Python, SQL, and related tools to ingest, transform, and prepare data. • Assist in optimizing data workflows for better performance, reliability, and cost-efficiency within Databricks environments. • Support the creation and maintenance of data models, tables, and integrations in cloud platforms (Azure, AWS, or similar). • Work closely with cross-functional teams (data analysts, scientists, and engineers) to deliver clean, accessible data for analytics and reporting. • Monitor data pipelines, troubleshoot basic issues, and contribute to documentation and best practices. • Stay curious about new Databricks features and data engineering trends to support ongoing improvements.