Job Summary: We are seeking a highly skilled Data Engineer with expertise in dashboard development, data modeling, and machine learning within the pharmaceutical industry. The ideal candidate will have deep hands-on experience creating end-to-end Power BI dashboards independently, hold relevant certifications, and possess strong programming skills in Python, R, and SQL. Job Responsibilities: Analyze large-scale pharmaceutical manufacturing datasets to generate actionable insights. Develop and implement predictive models to evaluate and improve process performance. Collaborate with chemists, engineers, and other cross-functional teams to support data-driven decisions. Apply machine learning algorithms to optimize pharmaceutical process development and manufacturing workflows. Design, develop, and maintain Power BI dashboards and semantic models using Power BI Fabric. Create clear, impactful visualizations and presentations to communicate findings to stakeholders. Support strategic planning by providing insights through data storytelling and reporting. Required Skills: Minimum 3 years of hands-on experience in developing Power BI dashboards and presentations independently (not as part of a team effort). Strong expertise in Power BI Fabric, semantic models, and data modeling. PL-300 certification (Microsoft Power BI Data Analyst Associate). Power BI Fabric certification. Proven experience using Power BI in the pharmaceutical industry, with a sound understanding of its data and compliance environment. Proficiency in Python, R, and SQL for data analysis and automation tasks. Experience using machine learning frameworks such as TensorFlow or PyTorch. Preferred Skills: Strong communication and stakeholder engagement skills. Experience in visual storytelling and building executive-level dashboards. Understanding of GMP compliance and data integrity standards in pharmaceuticals. Certifications: PL-300Power BI Fabric CertificationPython Certification Education: Master’s degree in data science or computer science (recent graduate preferred)