Data Engineer - Ia / Data

Hybrid work model in Madrid.

Permanent contract.

Stable and long-term technological project.

Participation in projects related to Data and Artificial Intelligence.

Technological environment and possibilities for professional growth.

Continuous training plan.

Health insurance.

Dental insurance.

Restaurant tickets.

Nursery Check.

Continuous training plan.

If you are a Data Engineer and want to continue growing professionally in projects related to data, analytics, and Artificial Intelligence, this could be your opportunity.

Professional experience as a Data Engineer or in similar positions.

Experience working with Python and SQL.

Experience with Apache Spark.

Solid knowledge of ETL/ELT and data pipeline development.

Experience with Kafka or equivalent technologies.

Knowledge of SQL/NoSQL databases and distributed storage.

Experience in Cloud environments.

Knowledge of Docker, containers, and CI/CD.

Knowledge of Infrastructure as Code.

• Design and develop batch and streaming data pipelines.
• Integrate structured and unstructured data sources.
• Implement ETL/ELT processes, guaranteeing data quality and reliability.
• Develop transformation and processing processes using Python, SQL, and Spark.
• Integrate different systems and sources via APIs.
• Work with Kafka or other equivalent technologies.
• Manage information using SQL/NoSQL databases and distributed storage.
• Automate deployments and operations of data platforms.
• Work with Cloud technologies, containers, and CI/CD.
• Apply Infrastructure as Code (IaC) practices.
• Optimize the performance, availability, and costs of the platforms.
• Manage schemas, metadata, and data lineage.
• Implement error handling and monitoring mechanisms.
• Apply DataOps, data quality, and data security best practices.

Valuable experience in DataOps, data quality, governance, and security.

At Infortec Consultores we continue to grow and are looking to hire a Data Engineer to participate in technological projects related to Data, Analytics, and Artificial Intelligence.

We are looking for a profile with experience in data engineering, with the ability to build and operate robust, scalable, and reliable data platforms and pipelines, working with different information sources and making data available for analytics solutions, AI, and business processes.

Design and develop batch and streaming data pipelines.

Integrate structured and unstructured data sources.

Implement ETL/ELT processes, guaranteeing data quality and reliability.

Develop transformation and processing processes using Python, SQL, and Spark.

Integrate different systems and sources via APIs.

Work with Kafka or other equivalent technologies.

Manage information using SQL/NoSQL databases and distributed storage.

Automate deployments and operations of data platforms.

Work with Cloud technologies, containers, and CI/CD.

Apply Infrastructure as Code (IaC) practices.

Optimize the performance, availability, and costs of the platforms.

Manage schemas, metadata, and data lineage.

Implement error handling and monitoring mechanisms.

Apply DataOps, data quality, and data security best practices.