Databricks Data Engineer

Responsibilities Design, build, and maintain scalable data pipelines to ingest, process, and transform structured and unstructured data Develop and optimize ETL/ELT processes to ensure high data quality, consistency, and reliability Work closely with business stakeholders, analysts, and data scientists to understand data requirements and deliver actionable datasets Architect and manage data lakes, warehouses, and cloud-based data platforms (e.g., Azure) Implement data models, schemas, and data integration solutions aligned with business needs Ensure data governance, security, and compliance standards are followed across all data assets Monitor pipeline performance and troubleshoot data-related issues to ensure system stability and uptime Automate data workflows and enable real-time or near-real-time data processing where required Optimize storage, compute, and processing costs while maintaining performance efficiency Stay updated with emerging data engineering tools, technologies, and best practices to drive continuous improvement Qualifications: 4+ years of experience in Data engineering, Databricks. Proven knowledge of data engineering tools: SQL, Python, Spark, Databricks (Delta Lake). Experience with SQL/NoSQL databases and Azure Data Lake Storage. Skills in building data models, APIs, and applications using SQL, Python, and. NET. Familiarity with Azure infrastructure, networking, and security. Experience with data visualization tools such as Power BI, Grafana, or Tableau