20 days ago
Remote, Mexico or Aguascalientes, MexicoMid Level
Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines using Python and Databricks.
- Develop data processing and transformation solutions with Spark and PySpark.
- Build, optimize, and maintain Databricks notebooks, workflows, and jobs.
- Integrate data from databases, APIs, files, and cloud storage, including cleansing, enrichment, and validation.
- Optimize data pipelines and Spark workloads for performance, scalability, reliability, monitoring, logging, and troubleshooting.
- Collaborate with analysts, developers, architects, and business teams on reviews, testing, documentation, CI/CD, and production support.
Requirements
- Strong hands-on experience with Python, Databricks, Spark, and PySpark.
- Experience building and supporting production-grade ETL/ELT data pipelines.
- Strong SQL skills and experience with data modeling, data transformation, and data quality practices.
- Experience with Delta Lake and Lakehouse architectures.
- Experience integrating data from databases, APIs, files, and cloud storage.
- Understanding of Git, CI/CD, testing, and engineering best practices.
Benefits
- Meaningful projects using technology to solve real-world challenges.
- Continuous learning through internal academies, certifications, and mentorship.
- Professional communities supporting connection and career growth.
- Remote work model in Mexico.
- Access to Capgemini offices in Mexico City, Aguascalientes, and Guadalajara for collaboration when needed.
Tech Stack
Categories
Data Engineering
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.