Key ResponsibilitiesDesign and implement ETL/ELT processes to ensure efficient data flow and transformation across our platforms.Utilize Databricks for data processing and analysis, optimizing performance and scalability.Administer data governance practices to maintain data integrity and compliance.Integrate APIs for seamless data exchange between various systems and tools.Collaborate with cross-functional teams to understand data needs and contribute to agile workflows.Monitor and optimize cloud storage solutions to ensure effective data storage and retrieval.Participate in CI/CD processes to streamline deployments and enhance code quality.Required and Preferred QualificationsProven experience with Databricks, ETL/ELT processes, and data governance in a professional setting.Strong proficiency in PySpark and SQL for data manipulation and querying.Experience with API integration and cloud storage solutions.Familiarity with Agile methodologies and CI/CD practices.Minimum of  5-6 years of relevant professional experience in data engineering.Our team fosters a culture of growth and innovation, encouraging continuous learning and professional development. We believe in a modern workplace that promotes collaboration, creativity, and flexibility. As a part of our team, you'll have access to mentoring programs, training sessions, and various resources to enhance your career trajectory.This role involves working closely within a cross-functional team, reporting directly to the Data Engineering Manager. You will collaborate with data scientists, business analysts, and IT specialists to ensure our data systems meet the needs of our organization.If you are passionate about data engineering and eager to make a significant impact, we invite you to apply for this exciting opportunity!