Apply to Engineer – Biotech Process Equipment Digital Automation, APIs/PLC/Python - (JP16092))

Job Title: Engineer – Biotech Process Equipment Digital Automation, APIs/PLC/Python - (JP16092)
Location: New Albany, OH. 43054
Employment Type: Contract
Business Unit: Site Process Development
Duration: 1+ year (with likely extensions and/or conversion to permanent)
Posting Date: 11/5/26
Pay Rate: $30 - $35/hour W2
Notes: Only qualified candidates need apply. 100% Onsite. Shift: 8-5 local hours. Must be flexible and available to support 1st, 2nd, or 3rd shift schedules as needed to ensure continuous, 24-hour coverage of Process Development activities at our packaging facility. Open to candidates with internship experience.

3 Key Consulting is hiring a Digital Process Development Engineer – Manufacturing Automation & Data Integration for a consulting engagement with our direct client, a leading global biopharmaceutical company.

Job Description:
Support the development and implementation of digital tools for manufacturing and process development. Work with engineering, automation, and technology teams to automate verification activities, manage equipment and process data, improve access to technical information, and connect product and manufacturing information throughout its lifecycle.

Apply programming, data integration, and emerging technologies to practical manufacturing challenges while gaining hands-on experience with equipment characterization, engineering runs, and manufacturing processes. Work alongside Process Development, Operations, engineering, and technology specialists to deliver tools and process improvements that strengthen efficiency, data quality, and engineering decision-making.

This role combines hands-on programming and engineering problem-solving with direct support of Process Development activities on the manufacturing line. The engineer will participate in equipment and process characterization, engineering runs, troubleshooting, data collection, and other line-based studies under the guidance of experienced PD staff. This hands-on experience will build practical knowledge of equipment and process behavior and inform the development of useful, reliable digital tools.

The engineer will take defined engineering needs through requirements development, implementation, testing, documentation, and handover, with guidance from the Process Development lead and collaboration with technical specialists in a regulated manufacturing environment.

Must be flexible and available to support 1st, 2nd, or 3rd shift schedules as needed to ensure continuous, 24-hour coverage of Process Development activities at our packaging facility.

Why is the Position Open?
Planned Project.

Top Must Have Skills:

Programming and Data Integration: Hands-on experience developing and supporting Python applications, SQL queries, APIs, and data processing workflows to build and troubleshoot practical engineering tools.
Manufacturing and Process Development: Understanding of manufacturing equipment, process parameters, and automation concepts, with the ability and willingness to support characterization, engineering runs, and other Process Development activities on the manufacturing line.
Engineering Delivery and Documentation: Ability to translate engineering needs into clear requirements, systematically investigate problems, implement and test solutions, analyze data, and document results through cross-functional collaboration.

Day to Day Responsibilities:

Contribute to both digital engineering projects and hands-on Process Development activities on the manufacturing line. Build practical knowledge of equipment, materials, and process behavior through direct participation in line activities, and use that experience to develop useful engineering tools.
Support equipment and process characterization, engineering runs, and other Process Development studies on manufacturing lines under the guidance of experienced PD staff.
Assist with study planning, protocol preparation and execution, observation of line performance, collection and analysis of process data, troubleshooting, and documentation of results in accordance with applicable site procedures.
Work alongside 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.

Success will be demonstrated through effective support of line activities, growing understanding of manufacturing processes, clear technical documentation, and reliable tools that meet agreed requirements and can be maintained and used by others.

Basic Qualifications:
Master degree OR Bachelor degree and 2 years of experience OR Associate degree and 6 years of experience OR High school diploma / GED and 8 years of experience

Preferred Qualifications:

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 is beneficial.
Candidates are not expected to have experience with every technology listed. Strong engineering judgment, hands-on development skills, and the ability to learn unfamiliar systems are essential.

Employee Value Proposition:

Red Flags:

Cannot clearly explain personal contributions to a software, data integration, or engineering automation project.
Cannot demonstrate a systematic approach to debugging, data comparison, or investigating discrepancies.
Does not address testing, incorrect or missing data, source traceability, or maintenance when describing a delivered tool.
Difficulty translating an engineering problem into clear requirements or explaining technical findings to cross-functional partners.
Limited attention to documentation, version control, change management, or appropriate human review of AI-assisted outputs.
Unwillingness to incorporate feedback or work collaboratively with engineering, automation, technology, and Quality partners.
Lack of experience with a specific preferred platform alone should not exclude a candidate who demonstrates the core skills and ability to learn.

Interview process:
2 Stages of interview(All virtual)

Initial Screen: Review relevant engineering and programming experience, interest in manufacturing applications, and assignment expectations.
Technical Interview (approximately 60 minutes): Walk through a tool or integration the candidate personally delivered. Discuss requirements, design choices, troubleshooting, testing, documentation, maintenance, and cross-functional collaboration. Practical Exercise: Use synthetic equipment or process parameter data to assess data comparison, discrepancy identification, handling of missing or incorrect values, and the candidate's approach to testing. Avoid requests for confidential work from a prior employer.
Team Discussion / Site Tour (optional): Discuss collaboration, communication, learning unfamiliar systems, and the manufacturing environment. Interview scheduling will be coordinated with selected candidates.

We invite qualified candidates to send your resume to resumes@3keyconsulting.com. If you decide that you’re not interested in pursuing this particular position, please feel free to take a look at the other positions on our website www.3keyconsulting.com/careers. You are also welcome to share this opportunity with anyone you think might be interested in applying for this role.