Senior Technical Lead
HCLTech
Madrid, Madrid, SpainPosted 24 days agoDiscoveredMatch locked
Senior Data Engineer (Python & Data Platforms)
- Extensive hands-on experience developing enterprise-grade solutions in Python, with advanced expertise in Pandas and NumPy. • Strong background in data engineering, including data ingestion, preprocessing, cleansing, transformation, validation, and enrichment. • Design and implementation of scalable and maintainable ETL/ELT pipelines. • Development of reusable frameworks and components for large-scale data processing. • Optimization of data pipelines for performance, reliability, and operational efficiency. • Application of software engineering best practices, including clean code, modular design, testing, and code reviews. • Experience working with large and complex datasets in production environments. • Ability to transform analytical prototypes into production-ready solutions. • Strong understanding of DevOps principles and software delivery lifecycle. • Design and maintenance of CI/CD pipelines for automated build, test, deployment, and release processes. • Experience creating and managing Python deployment artifacts, packages, and libraries. • Implementation of monitoring, logging, alerting, and observability capabilities for production services. • Experience supporting and troubleshooting applications in production environments. • Familiarity with cloud platforms (Azure and/or other cloud environments) • Strong stakeholder management and ability to collaborate with multidisciplinary teams. • Results-oriented mindset focused on scalability, robustness, security, and operational excellence. • Proven ability to take solutions end-to-end, from development through industrialization, deployment, and ongoing support. • Agile methodology Profile Summary: We are looking for a highly experienced Senior Data Engineer with deep expertise in Python, Pandas, and NumPy, combined with strong Data Engineering and DevOps capabilities. The successful candidate will be responsible for designing, building, and industrializing data solutions, ensuring they are scalable, reliable, and fully operationalized in production environments through modern software engineering and CI/CD practices.
Key Responsibilities
- Extensive hands-on experience developing enterprise-grade solutions in Python, with advanced expertise in Pandas and NumPy. • Strong background in data engineering, including data ingestion, preprocessing, cleansing, transformation, validation, and enrichment. • Design and implementation of scalable and maintainable ETL/ELT pipelines. • Development of reusable frameworks and components for large-scale data processing. • Optimization of data pipelines for performance, reliability, and operational efficiency. • Application of software engineering best practices, including clean code, modular design, testing, and code reviews. • Experience working with large and complex datasets in production environments. • Ability to transform analytical prototypes into production-ready solutions. • Strong understanding of DevOps principles and software delivery lifecycle. • Design and maintenance of CI/CD pipelines for automated build, test, deployment, and release processes. • Experience creating and managing Python deployment artifacts, packages, and libraries. • Implementation of monitoring, logging, alerting, and observability capabilities for production services. • Experience supporting and troubleshooting applications in production environments. • Familiarity with cloud platforms (Azure and/or other cloud environments) • Strong stakeholder management and ability to collaborate with multidisciplinary teams. • Results-oriented mindset focused on scalability, robustness, security, and operational excellence. • Proven ability to take solutions end-to-end, from development through industrialization, deployment, and ongoing support. • Agile methodology
Skill Requirements
We are looking for a highly experienced Senior Data Engineer with deep expertise in Python, Pandas, and NumPy, combined with strong Data Engineering and DevOps capabilities. The successful candidate will be responsible for designing, building, and industrializing data solutions, ensuring they are scalable, reliable, and fully operationalized in production environments through modern software engineering and CI/CD practices.
Other Requirements
Python, Pandas Numpy, Data engineering DevOps
Not included in the source posting: about the role, benefits.
Skills
pythondevopsnumpypandasci-cdagileazureetl
Who can apply
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