Python Data Engineer

We are seeking a passionate and skilled Data Engineer to join our dynamic US OBU Pelican report engineering team. In this role, you will be responsible for designing, building, and maintaining scalable and efficient data pipelines and workflows that support essential business reporting and analytics functions. This is a collaborative and impactful role, where your contributions will directly influence data-driven decision-making across the organization.
As a Data Engineer, you will design, develop, and optimize data pipelines using SQL and Python, ensuring they are robust and efficient for handling large volumes of data. You will leverage platforms such as Databricks to implement complex data transformation logic and collaborate closely with cross-functional teams to gather data requirements and deliver high-quality solutions. While experience with Airflow and DAG development is not mandatory, familiarity with these tools is considered an advantage. A critical part of your responsibilities will include ensuring the quality, integrity, and consistency of data across systems, as well as monitoring, troubleshooting, and resolving pipeline performance issues. You will also be expected to document your technical solutions and contribute to maintaining best practices in data engineering. Required Skills and Qualifications: The ideal candidate will have 3 to 5 years of experience in a Data Engineering or similar role, with strong proficiency in SQL for data extraction, transformation, and analysis, as well as hands-on experience using Python for data manipulation and scripting. Experience working with Databricks or similar big data platforms is essential, and a solid understanding of data warehousing concepts and ETL/ELT processes is expected. Familiarity with Apache Airflow and developing DAGs is a plus. The role also requires strong problem-solving abilities, excellent attention to detail, and effective communication and collaboration skills. Preferred Qualifications: Experience in the healthcare or pharmaceutical domain is highly desirable. Exposure to cloud platforms such as Azure or AWS, along with a working knowledge of CI/CD practices in the context of data engineering, would be an added advantage.