Packaging Data Engineer

About Marks

As the world's first Brand Creation Platform, we operate at the intersection of all things brand impact, from culture to commerce, ideation to activation, URL to IRL. Redefining how brands show up, evolve, and thrive, our Platform rewires the brand-creation ecosystem and shortens the runway from idea to impact by tech-fusing talent into one responsive team.

Position overview

The Packaging Data Engineer will report directly to the Global Head of Engineering and collaborate closely with engineering and client teams. The role will build and manage data systems that support packaging development, sustainability initiatives, and supply chain optimization. This role bridges packaging engineering and analytics by transforming packaging, materials, and operational data into scalable insights that drive decision-making for clients. Key responsibilities include developing innovative data analytic tools, managing packaging specification data for clients, and establishing the agency as a strategic technical leader in global Extended Producer Responsibility (EPR) legislation. Creative problem solving and attention to detail are essential for success in this position. As a vital member of the Marks Engineering team, you will significantly influence the future direction of the company's sustainability initiatives.

This is a hybrid role in Chicago

Responsibilities

• Collaborate closely with engineers, designers, and client service to ensure projects are delivered on time, within budget, and to the agency's quality standards.
• Lead the development of a central packaging database, automated EPR and sustainability reporting across regions, and data analytics tools such as cost versus performance optimization dashboards.
• Conduct research and stay up to date on the latest extended producer responsibility legislation, sustainability trends, and technology advancements in sustainability related to clients' needs and business goals.
• Identify and implement new technologies, data models, and packaging innovations to enhance the internal team's knowledge and expertise in sustainability.
• Confidently convey ideas, data-driven insights, and engineering concepts to internal and client team members, articulating and defending rationale behind decisions and recommendations.
• Analyze and assess global packaging portfolios, including identification of opportunity areas and recommendations for improving recyclability, plastic source reduction, and compliance.
• Enable dashboards and analytics for cost optimization, packaging performance, and sustainability reporting.
• Establish data governance and standards for packaging data structures, naming conventions, and version control.
• Support regulatory and compliance data requirements, document workflows, and ensure traceability of packaging decisions.
• Understand the strategic rationale, design intent, and technical feasibility behind solutions.
• Foster a positive and collaborative work environment that promotes creative problem solving, innovation, and continuous improvement.

Qualifications

• Bachelor's degree in packaging, mechanical, or manufacturing and design engineering or related technical field. 3-7+ years in packaging, data engineering, analytics engineering, or supply chain data roles.
• Experience working with manufacturing, product, or packaging datasets (preferred).
• Strong analytical and problem-solving skills.
• Detail-oriented with a focus on data accuracy and integrity.
• Strong experience and expertise in Excel, data management, and analytics. Experience with Python, data pipelines, cloud platforms, data modeling, and Microsoft Copilot a plus.
• Experience working with packaging specification databases, including data management and analysis.
• Understanding of packaging specifications, materials, lifecycle, BOMs, PLM/ERP systems, LCA, EPR, recyclability frameworks, and supply chain optimization.

About Propelis: Propelis is a portfolio of global marketing services and technology companies with a combined legacy of 150+ years, 2,000+ clients, 9,000 employees, and operations across 30 countries. Propelis provides the scale and support of a global organization while preserving the unique culture and identity of each company in its portfolio.

For more information visit: www.MakeMarks.com

EEO Statement: We are proud to be an equal opportunity workplace. All employment is decided on the basis of qualifications, merit, and business need. We offer equal employment opportunities to employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, genetic information, age, disability or any other characteristic protected by federal, state or local law.Equal Opportunity Employer Minorities/Women/Veterans/Disabled.

We strive to make our employment website and application process accessible to all users and applicants. In doing so, we provide reasonable accommodations to applicants with disabilities. If you have a disability and require a reasonable accommodation or assistance completing the application process, please contact a member of our Human Resource Team.

Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $90,000 USD - $100,000 USD annually. Ultimately, in determining pay, we will consider the successful candidate's location, experience, and other job-related factors.

Group benefits currently include a selection of health care plans with prescription drug coverage, dental plan, vision plan, basic and supplemental life insurance, a flexible spending account for medical and dependent care expenses or a health savings account based on plan selection, short/long term disability and 401(k) Savings Plan.

#LI-SM1 #LI-DNP

Bachelors of Engineering (required)

3 - 7 years: Years in packaging, data engineering, analytics engineering, or supply chain data roles (required)
Strong experience and expertise in Excel, data management, and analytics. Experience with Python, data pipelines, cloud platforms, data modeling, and Microsoft Copilot a plus. (preferred)
Experience working with manufacturing, product, or packaging datasets (preferred)