Junior Industrial Data & AI Engineer

Tasks & Duties

• Support data flows from production systems and machine-connected sources.
• Help develop technical interfaces, event structures, schema validation, and data-quality checks.
• Keep data traceable, dependable, and ready for analytics and AI use.
• Build scripts, automation helpers, and technical documentation.
• Use AI tools to speed up analysis, coding, documentation, and test support.
• Help prepare data for monitoring, prediction, and operational insights.
• Take part in troubleshooting and improving the data layer.
• Work with event-driven flows and support MQTT data exchange when needed.
• Bring forward ideas and challenge assumptions in a constructive way.
• Work with internal and external stakeholders, including colleagues abroad when needed.

Challenges

• Working in a real industrial environment where data quality, reliability, and traceability have direct consequences.
• Learning quickly while remaining independent and productive.
• Bridging what happens on machines with structured data and AI-ready design.
• Using AI responsibly to improve day-to-day productivity.
• Solving practical problems when there is no textbook answer.
• Supporting a platform that must be stable enough for operations today and future AI use cases.

Responsibilities / Accountabilities

• Deliver dependable technical work with a good level of independence.
• Follow standards for data validation, traceability, and governance.
• Help create industrial data flows that support future AI use cases.
• Raise issues early and communicate them clearly.
• Stay curious, constructive, and willing to learn.

Education

• Bachelor's degree, technical diploma, or equivalent practical experience in software engineering, information systems, or a related technical discipline.

Professional Experience

• 1–3 years of relevant experience, or comparable internship and project experience.
• Background in software development, data engineering, industrial IT, automation, or a similar technical field.
• Experience working with real systems is preferred.
• Exposure to industrial data, IoT, operational systems, or event-driven applications is an advantage.
• Ability to learn quickly and work independently.

Expertise

• Practical experience using AI tools for coding, analysis, documentation, testing, or research.
• Good programming or scripting skills, ideally in Python and SQL.
• Basic understanding of APIs, structured data, databases, and troubleshooting.
• Ability to work with logs, validate data, and reason about system behavior.
• Familiarity with Git, Linux, and common development workflows.
• Clear written communication and solid documentation habits.

Languages

·       Fluent English (Witten & oral)