Systems Integrations Analyst

Graham Packaging Company•West Hempfield Township, PA

8d•$81,500 - $122,300•Hybrid

About The Position

Graham 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.

Requirements

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%)
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

Nice To Haves

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
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

Responsibilities

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
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
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
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