What makes you a great fit :

• Design, develop, and maintain scalable and robust data pipelines using Python, SQL, Airflow, and dbt.
• Build and optimize data workflows and data integration processes.
• Ensure data quality, consistency, and reliability across various data sources.
• Implement and manage ETL processes to support data analytics and business intelligence.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs.
• Work with cloud platforms (AWS or Azure) to manage and scale data infrastructure.
• Monitor and troubleshoot data pipelines and workflows to ensure smooth operations.
• Implement best practices for data security, privacy, and compliance.
• Stay updated with the latest trends and technologies in data engineering and recommend improvements to existing processes and tools.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 7 to 15 years of experience in data engineering or a related role.
• Proficiency in Python for data manipulation and automation.
• Strong SQL skills for querying and managing relational databases.
• Experience with workflow orchestration tools like Airflow.
• Proficiency with dbt (data build tool) for transforming data in the warehouse.
• Hands-on experience with cloud platforms such as AWS or Azure, including services like S3, RDS, Redshift, EC2, Azure Blob Storage, Azure SQL Database, etc.
• Familiarity with data warehousing concepts and technologies.
• Strong problem-solving skills and attention to detail.
• Familiarity with CI/CD pipelines and version control systems like Git.
• Excellent communication and collaboration skills