Descripción de la oferta
We are knowmad mood! We are a leading digital transformation company, constantly evolving and at the forefront of technology. Made up of over 3,000 creative, digital, and innovative people connected by a purpose and capable of creating connections with people all around the world. A responsible, flexible team with high adaptability to the needs of our clients and the market, while providing value, vision, creativity, expertise, professionalism, and passion for technology in every project. The values that guide our path and lead us to excellence are collaboration, innovation, commitment, fun, and trust. Join our team as a Senior Data Engineer and enjoy an innovative and collaborative work environment. Key Responsibilities: Design, develop, and optimize large-scale data pipelines using Apache Spark and Python/PySpark. Create reliable, reusable, and well-structured datasets for business and analytical consumption. Develop and maintain cloud-based data solutions on Microsoft Azure. Process, transform, store, and expose data efficiently across different platforms and applications. Implement data quality controls, validation processes, monitoring, and documentation standards across data pipelines. Collaborate with Data Engineering, Data Science, Architecture, and business teams to understand requirements and deliver practical data solutions. Contribute to engineering best practices related to code quality, testing, version control, CI/CD, and automation. Apply data governance, data cataloging, and data quality monitoring practices to ensure trusted and compliant data assets. Participate in the design of scalable cloud-based data architectures. Professional Experience: 5+ years of experience in Data Engineering. 5+ years of hands-on experience with Apache Spark using Python/PySpark in production environments. Proven experience building and maintaining production-grade data pipelines in large-scale or complex data ecosystems. Strong understanding of dimensional data modeling and data warehouse design principles. Experience designing scalable cloud-based data architectures. Ability to provide technical guidance and support on ETL/ELT best practices and data engineering standards. Nice to Have: Experience with Databricks, Delta Lake, Unity Catalog, and Databricks Workflows. Hands-on experience delivering data engineering solutions using Azure Databricks. Familiarity with data governance and data cataloging frameworks. What do we offer? -Permanent contract -Remote work model
