Senior / Mid Data Engineer (Databricks)

Join our dynamic Insights & Data team of over 400 professionals delivering data-driven solutions. We specialize in Cloud & Big Data engineering, building scalable architectures across AWS, Azure, and GCP. The team manages the full Software Development Life Cycle (SDLC) using modern frameworks, agile methodologies, and DevOps best practices.

• Hands-on experience in data engineering and capability to work independently on moderately complex tasks.
• Experience with Databricks in projects.
• Strong skills in Python for data transformation and automation.
• Experience with at least one cloud platform (AWS, Azure, or GCP) in a production environment.
• Proficient communication skills in English.

Nice to have:

• Solid SQL skills and understanding of data modeling.
• Exposure to CI/CD pipelines, Terraform, or other DevOps tools.
• Familiarity with streaming technologies (e.g., Kafka, Spark Streaming).
• Knowledge of cloud data storage solutions (e.g., Data Lake, Snowflake, Synapse).
• Relevant certifications (e.g., Databricks Certified Data Engineer Associate).

• Develop and maintain data processing pipelines using Databricks.
• Collaborate with senior engineers and architects to implement scalable data solutions.
• Work with cloud-native tools to ingest, transform, and store large datasets.
• Ensure data quality, consistency, and security in cloud environments.
• Participate in code reviews and contribute to continuous improvement initiatives.

Capgemini is committed to diversity and inclusion, ensuring fairness in all employment practices. Evaluations are based on qualifications and performance, not personal characteristics.