Digital Product Engineer/ Industrial IoT & Data

• Collaborate with product owners and business stakeholders to understand data requirements and translate them into technical specifications
• Identify where data can create strategic value for each product line — for example, predictive maintenance and equipment life forecasting that support sales and service strategy
• Integrate data/protocol from field devices, IoT gateways, vendor APIs, files, and databases into the Product Module
• Validate data semantics, units, timestamps, and metric definitions with domain engineers before building logic
• Verify data completeness, accuracy, and provenance, and perform root-cause analysis on data anomalies — distinguishing data issues from genuine equipment degradation
• Turn engineering rules and expert knowledge into explainable rule-based health scores, alerts, and predictive recommendations
• Develop data pipelines, business logic, and REST APIs using Python and SQL, integrated with our central enterprise platform
• Write test cases and validate results with domain engineers before customer use
• Produce Solution Design Documents, Data Contracts, Rule Cards, API documentation, and handover guides
• Support customer pilots — collect usage feedback and improve the module for the next product line

Qualifications

• Bachelor's degree or higher in Computer Engineering, Computer Science, Information Technology, Electrical/Electronics Engineering, Data Science, or a related field
• 1–3 years of experience in data engineering, backend development, or IoT solutions; a portfolio of real working projects is a strong plus (exceptional fresh graduates are welcome to apply)
• Hands-on Python and SQL skills, practical experience with REST APIs, and working knowledge of Git
• A systems-analysis mindset: able to break business requirements down into data structures and logic
• Interest in device/IoT, sensor, and time-series data, with willingness to learn industrial systems
• Evidence-based thinking: able to explain the reasoning behind every rule, never concluding from data without support
• Clear communication with both business and engineering stakeholders; asks questions when requirements or data are unclear
• Self-directed and accountable: able to take work from concept to a working demo or pilot
• Comfortable reading technical documentation in English