Systems Integrations Analyst

Systems Integration AnalystGraham 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.Integration DevelopmentBuild and maintain API integrations connecting industrial data platforms, quality databases, SQL data stores, and enterprise business systemsWrite Python scripts and services to extract, transform, and move production and quality data reliably between systemsDevelop and test data pipelines with proper error handling, logging, and documentation so they run without babysittingTroubleshoot integration failures across the full path: source system, network, credentials, transformation logic, destinationCross-Functional IT/OT CoordinationWork 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 levelNavigate the boundary between enterprise IT standards and plant-floor realities, and know when each appliesDocument system interfaces, data flows, and access requirements for audit and team continuityAI Project SupportPartner with the team's AI and analytics engineers to deliver the data foundations their models depend onPrepare, structure, and validate datasets used in machine learning projects targeting quality prediction and process improvementGrow your applied AI skills through direct project involvement, model deployment support, results validation, and pipeline automationContribute ideas: as part of the team you will help develop the specifications and support usersTeam ExecutionTake direction from senior integration engineers and deliver assigned workstreams with minimal reworkParticipate in plant visits to see production systems firsthand and validate integrations against real operationsCommunicate progress, blockers, and risks clearlyQualificationsRequiredBachelor's degree in Computer Science, Engineering, Information Systems, or a related field — or equivalent demonstrated experience2-6 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 courseworkExperience working in or with operational/industrial environments, or clear evidence of the systems mindset those environments requireWillingness to travel to manufacturing plant sites periodically (estimated 10-20%)PreferredDirect manufacturing, industrial, utilities, logistics, or similar operational-environment experienceFamiliarity with industrial data platforms (historians, MES) or industrial communication protocolsExposure to machine learning workflows: data preparation, feature engineering, or model deployment supportExperience navigating enterprise IT processes: access requests, change management, security reviewsSkillsRequiredPython: Solid working proficiency: requests, pandas, working with JSON/XML, writing scripts that run unattended; this is the core tool of the jobAPIs & 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 otherSQL & Databases: Comfortable querying and writing to relational databases; understanding of schemas, joins, and data types across systemsIT/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 preferredProblem Solving: Debugs methodically across system boundaries; comfortable when the answer is not on Stack Overflow because the system is 15 years oldAI Interest: Genuine motivation to grow into applied AI and machine learning work; foundational exposure through coursework, projects, or self-study is a plusPreferredManufacturing / OT: Direct experience in a manufacturing company or operational environment: MES, SCADA, historians, PLCs, industrial protocols (OPC-UA, Modbus), or plant-floor data systemsEnterprise Systems: Exposure to SAP, ERP data structures, or quality management systemsVisualization: Power BI or similar dashboard tooling for validating and presenting integrated dataThe 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.Compensation StatementThe expected salary range for the position described in this posting is made in accordance with the legal mandates of certain jurisdictions within the United States.

The final agreed-upon compensation is based on individual qualifications and experience.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.EEO DisclaimerGraham Packaging is an Equal Opportunity Employer.

All qualified applicants will receive consideration for employment without regard to race, color, sex (including pregnancy), sexual orientation, religion, creed, age, national origin, physical or mental disability, gender identity and/or expression, marital status, veteran status or other characteristics protected by law.