Cloud Data Engineer (Databricks / Spark)

As a skilled Databricks Data Engineer with 36 years of experience, your role will involve designing, developing, and optimizing cloud-based data solutions. You should have solid expertise in Databricks, PySpark, and modern data engineering practices, enabling you to build scalable data pipelines, support data migration initiatives, and deliver high-quality data solutions for business insights and analytics. Key Responsibilities: - Implement scalable data pipelines using Databricks, PySpark, and SQL. - Develop and maintain ETL/ELT pipelines using Databricks and PySpark. - Perform data migration, validation, and reconciliation activities. - Collaborate effectively with business and technical stakeholders. - Support deployment, monitoring, and troubleshooting of data pipelines. Qualifications Required: - Strong proficiency in PySpark and Spark SQL. - Extensive experience with RBAC and ABAC implementation. - Familiarity with Delta Lake, Delta Tables, and Databricks Workflows. - Knowledge of Unity Catalog, data governance frameworks, and access management principles. - Understanding of data warehousing concepts, dimensional modeling, and ETL/ELT frameworks. - Experience in data migration, data validation, and reconciliation. The company prefers candidates with knowledge of performance tuning and cost optimization in Databricks, and Databricks certifications are highly desirable. As a skilled Databricks Data Engineer with 36 years of experience, your role will involve designing, developing, and optimizing cloud-based data solutions. You should have solid expertise in Databricks, PySpark, and modern data engineering practices, enabling you to build scalable data pipelines, support data migration initiatives, and deliver high-quality data solutions for business insights and analytics. Key Responsibilities: - Implement scalable data pipelines using Databricks, PySpark, and SQL. - Develop and maintain ETL/ELT pipelines using Databricks and PySpark. - Perform data migration, validation, and reconciliation activities. - Collaborate effectively with business and technical stakeholders. - Support deployment, monitoring, and troubleshooting of data pipelines. Qualifications Required: - Strong proficiency in PySpark and Spark SQL. - Extensive experience with RBAC and ABAC implementation. - Familiarity with Delta Lake, Delta Tables, and Databricks Workflows. - Knowledge of Unity Catalog, data governance frameworks, and access management principles. - Understanding of data warehousing concepts, dimensional modeling, and ETL/ELT frameworks. - Experience in data migration, data validation, and reconciliation. The company prefers candidates with knowledge of performance tuning and cost optimization in Databricks, and Databricks certifications are highly desirable.