Your Position
You will work as a Data Engineer in the Predictive Maintenance team. This hybrid and multi-cultural team consist of Data scientists, Data Engineers, a DevOps engineer, a QA engineer, an Architect, an UX designer, a Scrum Master, and a Product Owner.
Through predictive solutions, the Digital Service Platform aims at optimizing customers’ assets usage and maintenance, impacting their performance, cost, and sustainability KPIs by expanding the lifetime of the components.
In your role, you will participate together with the other Data Engineers in solution design discussions led by our product architect, where your knowledge and input will be highly valued. You will collaboratively work with IT and business SMEs to ensure delivery of high-quality end-to-end data pipelines.
Your responsibilities
You will be developing, testing, and documenting the data (collection and processing) pipelines for Predictive Maintenance solutions. The data collection consists of (complex) data pipelines from (IoT) sensors and low/high level control components to our data platform.



When the data is in the cloud, it must be processed and made available as data products to our data scientists
Align implementation efforts with other back-end developers across multiple development teams
You will develop scalable data pipelines to transform and aggregate data for business use, following software engineering best practices. For these data pipelines you will make use of the best frameworks available for data processing like Spark. We are continuously improving on the solutions we use and encourage you to keep challenging the status quo
You develop our data services for customer sites towards a product, using (test & deployment) automation, componentization, templates, and standardization to reduce delivery time of our projects for customers. The product provides insights into the performance of our material handling systems at customers all around the globe
You will contribute to the d

📌 Data Engineer (India)
🏢 Enterprise Minds
📍 India