Data Engineer/Databricks

As a Databricks Engineer, your role involves designing and developing ETL pipelines using Azure Data Factory (ADF) for data ingestion and transformation. You will collaborate with Azure stack modules such as Data Lakes and SQL Data Warehouse to create robust data solutions. Your responsibilities will include writing SQL, Python, and PySpark code for efficient data processing, translating business requirements into technical designs, developing mapping documents, and communicating project status with stakeholders to ensure smooth project execution. Key Responsibilities: - Design and develop ETL pipelines using Azure Data Factory (ADF) for data ingestion and transformation. - Collaborate with Azure stack modules like Data Lakes and SQL Data Warehouse to build robust data solutions. - Write SQL, Python, and PySpark code for efficient data processing and transformation. - Understand and translate business requirements into technical designs. - Develop mapping documents and transformation rules as per project scope. - Communicate project status with stakeholders, ensuring smooth project execution. Qualifications Required: - 4-10 years of experience in data ingestion, data processing, and analytical pipelines for big data and relational databases. - Hands-on experience with Azure services such as Azure Data Lake Storage (ADLS), Azure Databricks, Data Factory, Synapse, and Azure SQL Database. - Experience in SQL, Python, and PySpark for data transformation and processing. - Familiarity with DevOps and CI/CD deployments. - Experience in the insurance or financial industry is preferred. Please share your resume with Venku.Reddy@Valuemomentum.com if you are interested in this opportunity.,