At Capgemini Engineering, the world leader in engineering services, we bring together a global 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 Description

Your Role:
- Design, build, and maintain data pipelines and ETL processes using Databricks and Apache Spark.
- Optimize data workflows for performance, scalability, and cost efficiency.
- Implement data Lakehouse architecture and manage data ingestion from multiple sources.
- Collaborate with data scientists and analysts to enable advanced analytics and machine learning workloads.
- Ensure data quality, governance, and security across all data assets.
- Monitor and troubleshoot Databricks clusters, jobs, and workflows.
- Integrate Databricks with cloud services (AWS,



Azure, or GCP) and other enterprise systems.
- Document processes, standards, and best practices for data engineering.

Your Profile:
- 3+ years of experience in data engineering or big data technologies.
- Hands-on experience with Databricks, Apache Spark, and PySpark.
- Strong knowledge of SQL, Python, and data modeling principles.
- Experience with cloud platforms (AWS, Azure, or GCP) and their data services.
- Familiarity with Delta Lake, Lakehouse architecture, and data governance.
- Understanding of CI/CD pipelines and DevOps practices for data workflows.
- Excellent problem-solving and communication skills.

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Capgemini is a general business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse gro

📌 Senior Data Engineer (Bogotá)
🏢 Capgemini
📍 Bogotá