Data Engineer

• Design, develop, and manage data pipelines in Databricks using Python and PySpark.
• Apply best practices in data management, integration, and cleansing to ensure high-quality, accurate data.
• Write and optimize complex SQL queries across Oracle and MS SQL Server environments.
• Develop data quality rules, transformations, and mappings to ensure compliance with business requirements.
• Support cloud-based data solutions (Azure, AWS, or GCP) with a focus on scalability and reliability.
• Collaborate with cross-functional teams to troubleshoot data issues and resolve production incidents.
• Implement CI/CD pipelines for data workflows and ensure smooth deployments.
• Participate in Agile Scrum ceremonies and contribute to sprint planning, execution, and delivery.
• Provide production support for critical data systems, ensuring minimal downtime and quick resolution of issues.

We are seeking a highly skilled Data Engineer with strong expertise in Databricks, Python, and PySpark to support enterprise data management initiatives. The ideal candidate will bring experience in data warehousing, integration, cleansing, and troubleshooting while working in Agile environments. This role requires strong problem-solving skills, production support expertise, and the ability to collaborate effectively across teams.