Data Engineer(Pyspark)

Capgemini is an AI-powered global business and technology transformation partner with nearly 60 years of heritage and over 420,000 team members in more than 50 countries. The company delivers end-to-end services and solutions with deep industry expertise and a strong partner ecosystem, leveraging capabilities across strategy, technology, design, engineering, and business operations. Capgemini reported 2025 global revenues of €22.5 billion.

• Hands-on experience in data engineering handling moderately complex tasks.
• Proficiency in PySpark and understanding of distributed data processing.
• Comfortable working with Python for data transformation and automation.
• Experience with relational and/or NoSQL databases.
• Clear and effective communication in English.

Nice to Have:

• Familiarity with cloud platforms (AWS, Azure, GCP).
• Solid SQL skills and understanding of data modeling.
• Experience with orchestration tools (e.g., Airflow, Prefect).
• Exposure to CI/CD pipelines and DevOps practices.
• Knowledge of streaming technologies (e.g., Kafka, Spark Streaming).
• Experience working with Databricks.
• Relevant certifications in data engineering or big data technologies.

• Design and implement robust data pipelines using PySpark.
• Process and transform large datasets efficiently in distributed environments.
• Collaborate with data architects and analysts to deliver high-quality data solutions.
• Ensure data quality, consistency, and performance across systems.
• Participate in code reviews and contribute to technical improvements.