Data Engineer to support Manufacturing Science and Technology team. This position will be integrated within the Process Science, Modeling, and Data group. The role focuses on utilizing Data Engineering methodologies to enable the analytics and modeling needed to enhance various advanced therapy manufacturing processes.
The successful candidate will collaborate with multidisciplinary teams, showcasing a strong analytical mindset and exceptional problem-solving abilities. This role offers a unique opportunity to work with forward-thinking professionals dedicated to making a transformative impact in the field of advanced therapies manufacturing.
This Data Engineer position offers a chance to contribute to cutting-edge advancements in manufacturing science within a globally recognized organization. If you are passionate about data engineering and eager to make a significant impact, we encourage you to apply.
Top Three Skills: 1. BS or MS in a technical field (computer science, data engineering, etc.) 2. Strong analytical mindset with knowledge in data science. 3. Exceptional problem-solving skills.
Key Responsibilities:
Design, implement, and optimize data pipelines and ETL processes to ensure efficient data flow across systems.
Develop and maintain code development tools, infrastructure, and CI/CD data pipelines to facilitate automated software deployment in a manufacturing environment.
Write and evaluate code for quality assurance, conducting thorough testing and performance analysis to enhance existing systems and applications.
Collaborate with software development teams to create seamless integrations with internal and external back-end systems.
Construct and maintain robust data architectures, including databases and real-time data processing systems.
Identify and evaluate new data acquisition opportunities to enhance the manufacturing process and analytics capabilities.
Design data processes for modeling, mining, and production, ensuring reliable data outputs for analytical needs.
Propose and implement strategies to improve data reliability, efficiency, and quality across all data systems.
Qualifications:
Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
Demonstrated experience in DevOps and DataOps, with proven capabilities in developing tools and frameworks for automated data pipelines.
Proficient in Python, with experience using testing and code analysis tools such as pytest and pylint for maintaining code quality.
Hands-on experience with CI/CD practices, version control systems, and Agile methodologies, particularly with Atlassian tools like Confluence and Jira.
Familiarity with database programming, both SQL and No-SQL based, to ensure efficient data handling.
Experience building and managing cloud data systems and data lakes, particularly in environments like Microsoft Azure and Databricks.
Strong verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
Proven ability to effectively collaborate within cross-functional teams, driving initiatives that support operational excellence.