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.
