Data Engineer @ ROCKWOOL GBS in ROCKWOOL GBS

You will join our “Factory of the Future” team of specialists within Group R&D. We are a team of passionate, skilled and knowledgeable colleagues who develop & implement the newest technologies for stone wool production. The “Factory of the Future” team is recently established with the aim of upgrading our production facilities with best in class OT & IT Solutions. We are proud to be word leaders in our industry, and we work hard to stay in this position. 

We’re currently building Data Science Team and you would be a part of it.

• 2+ years of experience in data engineering preferably for production Industry
• Experience working with relational and non-relational databases (SQL, NoSQL, Influx DB)
• Understanding of IT/OT convergence
• Expertise in data pipelines and ELT (Extract, Load, Transform) processes
• Proficient in data warehousing and data lake technologies
• Experience with big data (Kafka, Snowflake, SQL/Redshift)
• Strong understanding of data quality and cleaning techniques
• Familiarity with cloud platforms for data storage and processing

You will join our “Factory of the Future” team of specialists within Group R&D. We are a team of passionate, skilled and knowledgeable colleagues who develop & implement the newest technologies for stone wool production. The “Factory of the Future” team is recently established with the aim of upgrading our production facilities with best in class OT & IT Solutions. We are proud to be word leaders in our industry, and we work hard to stay in this position. 

We’re currently building Data Science Team and you would be a part of it.

,[Automate data flow for analysis of industrial processes., Design systems to store and access industrial data efficiently., Ensure data quality for ML models in industrial automation., Create real-time data visualizations for industrial operations., Engineer data infrastructure for deployment of machine learning, Support Data Science Team in creating robust and innovative AI solutions ]
Requirements: SQL, NoSQL, Data pipelines, Data Lake, Big Data, Snowflake, Redshift, Cloud platform, Data engineering, Relational database
Additionally: Sport subscription, Training budget, Private healthcare, Small teams, International projects, Bike parking, Free coffee, Canteen, Playroom, No dress code.