Python - (JP16092))

3 Key Consulting•New Albany, OH

1d•Onsite

About The Position

The Digital Process Development Engineer supports the development and implementation of digital tools for manufacturing and process development at a biopharmaceutical packaging facility. The role applies programming, data integration, and emerging technologies to practical manufacturing challenges, including automated verification, equipment and process data management, technical information access, and linking product and manufacturing information throughout its lifecycle. The position combines programming and engineering problem-solving with hands-on Process Development work on manufacturing lines. Under the guidance of experienced Process Development staff, the engineer participates in equipment and process characterization, engineering runs, troubleshooting, data collection, and other line-based studies. This experience informs the development of reliable digital tools and builds practical understanding of equipment and process behavior. The engineer takes defined engineering needs through requirements development, implementation, testing, documentation, and handover, working with Process Development, Operations, Quality, Automation, engineering, and technology partners in a regulated manufacturing environment. The role is onsite in New Albany, Ohio, and requires flexibility to support first-, second-, or third-shift schedules as needed for continuous 24-hour Process Development coverage.

Requirements

Meet one of the following education and experience combinations: master's degree; bachelor's degree and 2 years of experience; associate degree and 6 years of experience; or high school diploma/GED and 8 years of experience.
Demonstrate engineering judgment, hands-on development skills, and the ability to learn unfamiliar systems.
Be willing and available to support first-, second-, or third-shift schedules as needed for continuous 24-hour Process Development coverage.
Translate engineering needs into clear requirements, systematically investigate problems, implement and test solutions, analyze data, and document results through cross-functional collaboration.
Support manufacturing-line characterization, engineering runs, and other Process Development activities.

Nice To Haves

Practical experience developing and supporting Python applications, SQL queries, APIs, and data-processing workflows.
Familiarity with PLC tags, industrial data connectivity, and manufacturing historians.
Experience with data platforms such as Databricks, cloud data services, or dashboard and visualization tools.
Familiarity with product lifecycle management, engineering configuration management, or requirements traceability.
Experience applying AI tools to technical information retrieval, workflow automation, or engineering analysis, with appropriate testing and human review.
Working knowledge of version control, debugging, software testing, and change management.
Experience in pharmaceutical, biotechnology, medical device, or another regulated manufacturing environment.
Exposure to CAD, engineering simulation, or digital twin applications.
Internship experience is acceptable.

Responsibilities

Contribute to digital engineering projects and hands-on Process Development activities on manufacturing lines.
Support equipment and process characterization, engineering runs, and other Process Development studies under the guidance of experienced staff.
Assist with study planning, protocol preparation and execution, observation of line performance, process-data collection and analysis, troubleshooting, and documentation in accordance with site procedures.
Work with Operations, Quality, Automation, and engineering partners to investigate process issues and identify improvement opportunities.
Develop tools for automated verification, data comparison, and identification of discrepancies in engineering and manufacturing information.
Build and maintain solutions for managing equipment settings, process parameters, and configuration data.
Read and interpret equipment data from PLCs, historians, and other manufacturing systems in collaboration with automation engineers.
Develop data-processing workflows, pipelines, dashboards, and reporting tools; investigate data-quality issues and communicate findings.
Gather user requirements and take defined engineering needs through implementation, debugging, testing, documentation, and handover.
Support digital product lifecycle management by organizing and connecting product, component, equipment, and process information.
Develop AI-assisted tools for technical information retrieval, data analysis, and engineering documentation, with appropriate testing and human review.
Support modeling and simulation activities through engineering data preparation and integration with technical specialists.
Maintain source traceability, version-controlled code, test results, operating instructions, and handover materials consistent with applicable site procedures.