Data Engineer (External)

We are looking for a Data Engineer (External) to join Heidelberg Materials Digital Hub Varna.

Heidelberg Materials is one of the largest global building materials companies, providing the materials to build our future. Our future is sustainable. Our future is digital. And it goes way beyond cement, aggregates and ready-mixed concrete. With more than 51,000 employees in over 50 countries, we are known for our expertise and superior quality.

As an integral part of Heidelberg Materials, Digital Hub Varna drives the vision of becoming a leading technology company in the building materials sector. Here, innovation meets impact, empowering us to redefine the industry from within.

About the role:

We are looking for an experienced Data Engineer (External) who will join a new team, focused on delivering global solutions that support various sustainability initiatives and requirements. The team is built from the ground up and is highly international.

To strengthen our product teams, we are looking for a Data Engineer who will report to the Head of Software Sustainability.

Your next challenge:

• Build and maintain scalable data pipelines and ETL processes.
• Design, develop, and optimize data architectures and data models.
• Handle a broad range of tasks, from data aggregation and transformation to schema definition and API implementation.
• Advocate consistency and best practices in our data engineering architecture.
• Work closely with stakeholders, product owners, and other team members from various technical backgrounds to deliver high-quality data solutions that support business needs.
• Communicate complex data-related matters clearly and concisely to both technical and non-technical audiences.
• Convert abstract requirements and objectives into clear and actionable steps.
• Map business processes to data models and/or algorithms.
• Be proactive, persistent, and eager to deliver robust and scalable data solutions.

Your profile:

• Track record of designing and implementing scalable data solutions in cloud environments (preferably Azure).
• 3+ years of experience with Python, PySpark, and data engineering frameworks (Databricks, Synapse, or Microsoft Fabric).
• Proficiency in building and managing ETL pipelines and working with data orchestration tools like Azure Data Factory, Power Automate, or Apache Airflow.
• Experience in data modeling, data warehousing, and working with relational and NoSQL databases (PostgreSQL, time-series databases, etc.).
• Solid knowledge of algorithms and data structures with the ability to apply them to real-world problems.
• Hands-on experience with event-driven architecture and streaming technologies like Kafka.
• Familiarity with REST APIs, ODATA API, and microservices architecture.
• Experience with CI/CD pipelines, automated testing, and infrastructure-as-code tools.

Nice to Have:

• BSc or MSc in Computer Science, Data Engineering, or a related field. A PhD in a scientific, mathematical, or engineering discipline would be a plus.
• Experience with machine learning, data science, and advanced analytics.
• Familiarity with Web3 technologies such as blockchain, smart contracts, and NFTs.