At Capgemini Engineering, the world leader in engineering services, we bring together a general team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D; and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.
Job DescriptionResponsabilities
- Develop and maintain efficient ETL pipelines using Azure Data Factory and Databricks to process and transform large datasets for analysis.
- Analyze large datasets and build machine learning models using Python and Spark to extract actionable insights and solve business problems.
- Utilize Apache Spark to process and analyze large volumes of data in a distributed environment, ensuring scalability and performance.
- Deploy machine learning models to production using Azure and Databricks and monitor their performance for continuous improvement.
- Work closely with cross-functional teams (data engineers, business analysts, etc.) to understand requirements and communicate insights and results effectively to stakeholders.
Requirements:
- Advanced English skills (B2+)
- Experience in ETL and Azure tools: A minimum of 2-5 years of experience in developing ETL processes using Azure Data Factory, Azure Databricks, and other Azure cloud tools.
- Knowledge of Apache Spark and Databricks: Experience using Apache Spark for distributed data processing and knowledge of Databricks for data integration and transformation.
- Proficiency in Python and SQL: Advanced skills in Python for automating processes and manipulating data, along with a strong understanding of SQL for querying and transforming data.
- Handling large volumes of data: Ability to manage, transform, and optimize large volumes of data using cloud p
📌 Bilingual Azure Data Engineer (Bogotá)
🏢 Capgemini
📍 Bogotá
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