OverviewGraham Packaging is a leading North American manufacturer of rigid plastic containers, operating 270+ production lines across facilities throughout the US. Our manufacturing intelligence team connects real-time machine data, quality systems, and business applications into a unified data platform that drives measurable bottom-line returns.
We are hiring a Systems Integration Analyst to help deliver the next phase of that platform: integrating our production and quality data systems to enable AI-driven analytics. This is hands-on integration work; building API connections, moving data between industrial and enterprise systems, and working across IT and OT teams to make disconnected systems talk to each other.
You will work directly with our AI and analytics initiatives as part of the team. The integrations you build are what make our AI projects possible, and as the data foundation matures, you will have a direct path into applied AI and machine learning work.
Responsibilities
Integration Development
- Build and maintain API integrations connecting industrial data platforms, quality databases, SQL data stores, and enterprise business systems
- Write Python scripts and services to extract, transform, and move production and quality data reliably between systems
- Develop and test data pipelines with proper error handling, logging, and documentation so they run without babysitting
- Troubleshoot integration failures across the full path: source system, network, credentials, transformation logic, destination
Cross-Functional IT/OT Coordination
- Work with corporate IT teams on service accounts, database access, firewall rules, and infrastructure requests.
- Work with plant-side OT and controls resources to understand data sources at the machine and line level
- Navigate the boundary between enterprise IT standards and plant-floor realities, and know when each applies
- Document system interfaces, data flows, and access requirements for audit and team continuity
AI Project Support
- Partner with the team's AI and analytics engineers to deliver the data foundations their models depend on
- Prepare, structure, and validate datasets used in machine learning projects targeting quality prediction and process improvement
- Grow your applied AI skills through direct project involvement, model deployment support, results validation, and pipeline automation
- Contribute ideas: as part of the team you will help develop the specifications and support users
Team Execution
- Take direction from senior integration engineers and deliver assigned workstreams with minimal rework
- Participate in plant visits to see production systems firsthand and validate integrations against real operations
- Communicate progress, blockers, and risks clearly
Qualifications
Qualifications
Required
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field — or equivalent demonstrated experience
- 2-6 years of hands-on experience building integrations, data pipelines, or system-to-system connections in Python (internships and co-ops in operational environments count)
- Demonstrated experience working with REST APIs and SQL databases in real projects, not just coursework
- Experience working in or with operational/industrial environments, or clear evidence of the systems mindset those environments require
- Willingness to travel to manufacturing plant sites periodically (estimated 10-20%)
Preferred
- Direct manufacturing, industrial, utilities, logistics, or similar operational-environment experience
- Familiarity with industrial data platforms (historians, MES) or industrial communication protocols
- Exposure to machine learning workflows: data preparation, feature engineering, or model deployment support
- Experience navigating enterprise IT processes: access requests, change management, security reviews
Skills
Required
- Python: Solid working proficiency: requests, pandas, working with JSON/XML, writing scripts that run unattended; this is the core tool of the job
- APIs & Integrations: Hands-on experience calling and consuming REST APIs; understanding of authentication methods (API keys, OAuth, service accounts); experience connecting systems that were not designed to talk to each other
- SQL & Databases: Comfortable querying and writing to relational databases; understanding of schemas, joins, and data types across systems
- IT/OT Awareness: Understands that plant-floor systems are not cloud apps: legacy protocols, network segmentation, uptime constraints, and change control. Prior exposure to manufacturing, industrial, utility, or similar operational environments strongly preferred
- Problem Solving: Debugs methodically across system boundaries; comfortable when the answer is not on Stack Overflow because the system is 15 years old
- AI Interest: Genuine motivation to grow into applied AI and machine learning work; foundational exposure through coursework, projects, or self-study is a plus
Preferred
- Manufacturing / OT: Direct experience in a manufacturing company or operational environment: MES, SCADA, historians, PLCs, industrial protocols (OPC-UA, Modbus), or plant-floor data systems
- Enterprise Systems: Exposure to SAP, ERP data structures, or quality management systems
- Visualization: Power BI or similar dashboard tooling for validating and presenting integrated data
The standard compensation for this role is $81,500 - $122,300. Salary offers will be determined based on final candidate qualifications, experience, skillset, and other relevant factors.
Benefits StatementBenefits include medical, dental, vision and basic life insurance. Employees are able to enroll in the company’s 401K Employee Saving Plan and may participate in its Employee Wellness Program. Employees will also receive paid time off in accordance with company policy and state law requirements.
