Empleos de big data en Oviedo, Asturias provincia

ArcelorMittal is the world’s largest steel producer. We use the most innovative technology to create the steels tomorrow’s world will be made of. Every day over 190,000 of our talented people, located in over 60 countries, push the boundaries of digitalization and use advanced technology to create a world that is stronger, faster and smarter. To help make this possible, they know they can depend on the support and training that a company of our scope and scale can provide.

The Digitalization team is part of the ArcelorMittal R&D Spain Lab and it provides worldwide service within the ArcelorMittal Group. We are a team of more than 50 researchers working on Digitalization and Artificial Intelligence applied to a wide range of activities (manufacturing, product development, environmental, decarbonization, supply chain, commercial, planning & scheduling, etc.). This multidisciplinary team covers a wide variety of scientific and business areas with highly qualified researchers (engineers, mathematicians, physicists, etc.), all of them with deep expertise in combining Science and Business know-how. Their enthusiasm and commitment create an incredible working atmosphere for those that want to enjoy the experience of researching and applying breakthrough ideas in the real industrial world.

Your role

We are seeking a highly motivated and skilled data engineer to join our team. As a data engineer, you will be responsible for designing, building, and maintaining the infrastructure required for the collection, storage, processing, and analysis of large and complex data sets. You will work closely with data analysts, data scientists, and other members of the data team to ensure that our data infrastructure meets their needs and is scalable for future growth.
We are currently adopting the Data Mesh approach using the modern data stack. As a data engineer, you will be instrumental in designing and implementing our new data infrastructure. You will collaborate with other members of the data team to ensure that our data mesh implementation is consistent with industry best practices and is aligned with our business goals.

As data engineer, your missions will be:

• Design, build, and maintain data pipelines and infrastructure for large and complex data sets.
• Develop and implement data processing and storage solutions that are scalable and efficient.
• Collaborate with data analysts, data scientists, and other members of the data team to ensure that data is accurate, consistent, and available for analysis.
• Integrate with third-party APIs and services to enrich data sets and improve data quality.
• Ensure the security and compliance of the data, including data privacy laws and regulations.
• Monitor and optimize data infrastructure performance and troubleshoot issues as they arise.
Keep up to date with emerging trends and technologies in big data and cloud computing.
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If you are passionate about big data and cloud technologies and are looking for an exciting opportunity to work with a dynamic team of data professionals and help us adopt the Data Mesh architecture and modern data stack, please apply to join us as a data engineer.

Your profile
Requirements:

• Master degree in Computer Science or a related technical field.
• Programming skills in at least one of the following programming languages: Python, Java, Scala or SQL.
• Familiarity with big data technologies such as Spark, Flink and NoSQL databases.
• Knowledge of cloud technologies such as AWS, Azure, and Google Cloud Platform.
• Familiarity with data warehousing concepts and ETL/ELT tools.
• Strong problem-solving skills, attention to detail, and the ability to work independently.
Excellent communication and teamwork skills.

Desirable knowledge:

• Understanding of MLOps lifecycle and tools, such as MLFlow.
• Knowledge of DevSecOps methodologies and tools.
• Experience with containerization technologies such as Docker and Kubernetes.
• Experience with the Data Mesh architecture and modern data stack.
• Knowledge of data visualization and dashboarding tools.
• Experience with infrastructure-as-code technologies such as Terraform or Pulumi.
Familiarity with monitoring and logging tools.

What we will offer

Integration in a highly qualified group of researchers with the possibility of pursuing a career in the scientific area in the R&D organization of the world's largest steel producer.