Data Engineer | Senior Data Engineer | ETL | Spark | Databricks | Snow

Role & responsibilities - Design, develop, and maintain scalable data pipelines. - Build ETL/ELT workflows for structured and unstructured data. - Develop cloud-based data solutions using AWS, Azure, or GCP. - Implement data warehousing solutions for business reporting and analytics. - Optimize data processing jobs for performance and scalability. - Work with Apache Spark and Databricks for large-scale data processing. - Build and maintain workflows using Apache Airflow. - Ensure data quality, governance, and security standards. - Collaborate with Data Scientists, Analysts, and Software Engineers. - Participate in code reviews and follow development best practices. Preferred candidate profile - 3 to 7 years of experience in Data Engineering. - Strong knowledge of SQL and Python. - Experience in designing scalable data pipelines. - Hands-on experience with cloud platforms (AWS, Azure, or GCP). - Knowledge of Spark, Databricks, and modern data architectures. - Robust analytical and problem-solving skills. - Experience working in Agile development environments is preferred. Role & responsibilities - Design, develop, and maintain scalable data pipelines. - Build ETL/ELT workflows for structured and unstructured data. - Develop cloud-based data solutions using AWS, Azure, or GCP. - Implement data warehousing solutions for business reporting and analytics. - Optimize data processing jobs for performance and scalability. - Work with Apache Spark and Databricks for large-scale data processing. - Build and maintain workflows using Apache Airflow. - Ensure data quality, governance, and security standards. - Collaborate with Data Scientists, Analysts, and Software Engineers. - Participate in code reviews and follow development best practices. Preferred candidate profile - 3 to 7 years of experience in Data Engineering. - Strong knowledge of SQL and Python. - Experience in designing scalable data pipelines. - Hands-on experience with cloud platforms (AWS, Azure, or GCP). - Knowledge of Spark, Databricks, and modern data architectures. - Robust analytical and problem-solving skills. - Experience working in Agile development environments is preferred.