Senior Python Data Engineer — ETL, Pandas & NumPy

Hcltech; Córdoba; Presencial; EUR 50.000 - 80.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Learning and career development

Flexible work arrangements

Virtual-first work environment

Diversity and inclusion

Descripción de la vacante

HCLTech is seeking an expert Data Engineer to strengthen our Spain presence in Córdoba. You will design and implement enterprise-grade data solutions using Python with Pandas and NumPy, focusing on data ingestion, cleansing, transformation, and enrichment.

You will build scalable ETL/ELT pipelines, develop reusable data processing frameworks, and optimize pipelines for performance, reliability, and security. Agile methods and DevOps practices will guide production deployment and monitoring.

Formación

• Extensive Python development for enterprise-grade data solutions.
• Experience with data ingestion, cleansing, transformation and enrichment.
• Design scalable ETL/ELT pipelines for production environments.
• Develop reusable data processing frameworks and components.
• Implement monitoring, logging, and observability in production.
• Experience with CI/CD pipelines and DevOps practices.
• Ability to deploy and manage artifacts and libraries.

Responsabilidades

• Build and maintain ETL/ELT pipelines at scale.
• Transform prototypes into production-ready solutions.
• Collaborate with multidisciplinary teams and stakeholders.
• Ensure performance, reliability, and security of data platforms.
• Drive end-to-end delivery from development to production.

Conocimientos

Python

Pandas

NumPy

ETL/ELT

Data ingestion

CI/CD

DevOps

Azure

Production support

Agile

Descripción del empleo

HCLTech is seeking an expert Data Engineer to strengthen our Spain presence in Córdoba. You will design and implement enterprise-grade data solutions using Python with Pandas and NumPy, focusing on data ingestion, cleansing, transformation, and enrichment.

You will build scalable ETL/ELT pipelines, develop reusable data processing frameworks, and optimize pipelines for performance, reliability, and security. Agile methods and DevOps practices will guide production deployment and monitoring.