Databricks Data Engineer

Stack

Responsibilities

• ▹Design and implement data processing solutions using Databricks for large-scale and diverse datasets
• ▹Design, build, and enhance data pipelines with Python and cloud-native tools
• ▹Work closely with solution architects to define and uphold best practices in data engineering
• ▹Ensure data consistency, security, and scalability within cloud-based environments

Requirements

• ▹Strong experience in data engineering, with at least 1 year of hands-on Databricks expertise
• ▹Strong experience in Python for automation and data transformation
• ▹Experience working with at least one major cloud platform (AWS, Azure, or GCP)
• ▹Strong communication skills and strong English language skills

Nice to have

• ▹Solid understanding of SQL with experience in query optimization and data modeling
• ▹Familiarity with DevOps methodologies, CI/CD pipelines, and Infrastructure as Code (Terraform, Bicep)
• ▹Experience with real-time data streaming technologies such as Kafka or Spark Streaming
• ▹Knowledge of cloud storage solutions like Data Lake, Snowflake, or Synapse
• ▹Hands-on experience with PySpark for distributed data processing
• ▹Relevant certifications such as Databricks Certified Data Engineer Associate or other cloud-based data certifications

Soft skills

What we offer

• ▹Access to an education library with 250,000+ courses, certifications and learning resources
• ▹Global Well-being Hub
• ▹Hybrid work and flexible hours
• ▹Employee referral bonus and company shares program

About the company

The Capgemini Group is one of the world's leading players in IT services, digital transformation, and technology and engineering solutions, with a heritage of nearly 60 years, present in more than 50 countries with 420,000 employees.