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**Job Function: **
Technology Product & Platform Management
**Job Sub Function: **
Technology Operations Support
Job Category:
Scientific/Technology
All Job Posting Locations:
Beerse, Antwerp, Belgium
Job Description:
Summary
We are seeking a motivated Junior IT Engineer to support optimization of IT processes across Manufacturing, Labs, and Logistics services. The role focuses on enabling planning for technology lifecycle (site assets and software upgrades) by leveraging existing data in data lakes and AI/ML toolkits on J&J platforms. This is an entry-level role for someone with strong data fundamentals, practical scripting skills, and an interest in applying AI to operational IT challenges.
Key Responsibilities
Support collection, validation and basic transformation of asset and operations data from data lakes, CMDBs, and other source systems.
Assist in creating data pipelines and lightweight ETL processes to bring disparate data into analysis-ready formats.
Help develop dashboards, reports, and analytics to identify upgrade candidates, end-of-life hardware, software versions, and risk-prioritized upgrade windows.
Work with AI toolkits and low-code automation to prototype predictive analyses (e.g., failure risk, upgrade impact, compatibility).
Maintain and enrich asset inventories (hardware, firmware, software) and map them to site services and business owners.
Support lifecycle planning activities by producing data-driven recommendations for asset refresh, patching, and software upgrade sequencing.
Implement and test small automation workflows to streamline approval, scheduling, and status tracking for upgrades.
Collaborate with IT MLL service owners to gather requirements and communicate findings.
Document processes, SOPs, and data lineage for repeatability and audit readiness.
Required Skills
0–3 years of professional experience in IT, data engineering, or related field.
Practical scripting/programming skills (Python preferred; PowerShell or Bash acceptable).
Working knowledge of SQL for querying and joining datasets.
Experience working with structured data in data lakes or relational data sources (ability to read, clean, and join datasets).
Basic understanding of AI/ML concepts and how they can be applied to operational data (classification, regression, anomaly detection).
Familiarity with IT asset lifecycle concepts: CMDB, asset tagging, firmware/driver management, software versions, patching basics.
Ability to create clear visualizations and reports (Power BI, Tableau, or similar).
Strong problem-solving mindset and attention to data quality and detail.
Good written and verbal communication skills; able to explain technical findings to non-technical stakeholders.
Willingness to learn and follow J&J platforms and toolkits, security controls, and data governance policies.
Preferred Skills
Experience with cloud data platforms or data lake technologies (e.g., Azure Data Lake, S3) — exposure acceptable.
Familiarity with MLOps or model lifecycle basics (model training, validation, deployment, monitoring).
Knowledge of manufacturing, laboratory, or logistics operations and common OT/IT interfaces.
Experience with automation/orchestration tools (Azure Logic Apps, Power Automate).
Basic understanding of networking and system administration concepts (Linux/Windows).
Exposure to REST APIs and experience extracting data from API endpoints.
Behavioral & Interpersonal Skills
Collaborative team player; comfortable working across business and technical stakeholders.
Proactive learner who asks clarifying questions and seeks feedback.
Strong organizational skills and ability to manage multiple small initiatives.
Comfortable working in regulated environments with an emphasis on compliance and documentation.
Tools & Technologies (examples)
Languages: Python, SQL, PowerShell/Bash
Data/Analytics: Data lake formats, parquet/CSV, Power BI / Tableau
AI/ML: Basic use of Python ML libraries (scikit-learn, pandas), low-code AI toolkits on J&J platforms
Asset & ITSM: CMDB concepts, ticketing systems (ServiceNow or similar)
Automation: Scripting and lightweight workflow automation tools
What Success Looks Like (4 months)
Able to independently ingest and prepare asset datasets from the data lake for analysis.
Deliver at least few dashboards/reports that surface high-priority upgrade candidates and lifecycle recommendations and dashboard for project delivery, status (testing) of Project.
Automate a repeatable data quality check or a simple workflow that reduces manual steps in upgrade planning.
Demonstrate clear documentation of data sources, transformation logic, and an initial risk-prioritization method for upgrades.
Actively participate in cross-functional lifecycle planning meetings and present data-driven insights.
**Required Skills: **
Preferred Skills:
The anticipated pay range and benefits for this position is:
As this position is posted in a country that is subject to EU pay transparency requirements, the Talent Acquisition team will provide pay range information on request and to candidates invited to an interview.