Data Engineer
Technical skills
- Data pipeline development and orchestration.
- ETL/ELT frameworks and data integration tools.
- SQL and database management systems.
- Programming languages such as Python, Scala, or Java.
- Data warehousing and data lake architectures.
- Big Data technologies (Spark, Hadoop, Kafka).
- Cloud data platforms (AWS, Azure, Google Cloud Platform).
- Data modeling and database design.
- Data governance, quality, and security principles.
- CI/CD, DevOps, and Infrastructure as Code practices.
Soft skills
- Strong analytical and problem-solving abilities.
- Attention to detail and data quality focus.
- Effective communication and stakeholder collaboration.
- Ability to work in cross-functional and Agile environments.
- Adaptability to evolving technologies and business needs.
- Organizational and prioritization skills.
- Curiosity and continuous learning mindset.
- Ownership and accountability.
- Career Opportunities
- CTA to the offer
The Data Engineer designs, builds, and maintains scalable data architectures that enable organizations to collect, process, store, and analyze large volumes of data. They ensure the availability, reliability, and quality of data across the organization, providing the foundation for business intelligence, analytics, artificial intelligence, and data-driven decision-making.
Main activities
- Design, develop, and maintain data pipelines and ETL/ELT processes.
- Build and optimize data warehouses, data lakes, and data platforms.
- Integrate data from multiple internal and external sources.
- Ensure data quality, consistency, and governance across systems.
- Monitor and optimize data processing performance and scalability.
- Collaborate with Data Analysts, Data Scientists, Product Owners, and business stakeholders.
- Implement data security, compliance, and access management best practices.
- Support cloud migration and modernization initiatives within data ecosystems.
- Troubleshoot data-related issues and contribute to continuous platform improvements.
Technical skills
- Data pipeline development and orchestration.
- ETL/ELT frameworks and data integration tools.
- SQL and database management systems.
- Programming languages such as Python, Scala, or Java.
- Data warehousing and data lake architectures.
- Big Data technologies (Spark, Hadoop, Kafka).
- Cloud data platforms (AWS, Azure, Google Cloud Platform).
- Data modeling and database design.
- Data governance, quality, and security principles.
- CI/CD, DevOps, and Infrastructure as Code practices.
Soft skills
- Strong analytical and problem-solving abilities.
- Attention to detail and data quality focus.
- Effective communication and stakeholder collaboration.
- Ability to work in cross-functional and Agile environments.
- Adaptability to evolving technologies and business needs.
- Organizational and prioritization skills.
- Curiosity and continuous learning mindset.
- Ownership and accountability.
- Career Opportunities
- CTA to the offer
Application form
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