Data Engineer (Cloud)

Capgemini Global Insights & Data business line is a market leader in data, platform, and analytics across various sectors including financial services, consumer products, manufacturing, and life sciences. The organization is seeking an experienced and visionary Data Engineer (Cloud) to lead data-driven decision-making processes.

Work Conditions: Hybrid, Full-time

Your Role:

• Design, develop, and maintain scalable ETL (Extract, Transform, Load) pipelines using cloud-native tools.
• Implement best practices for data ingestion, transformation, and loading processes from multiple sources.
• Automate workflows and develop data pipelines using tools such as Apache Airflow, Glue, Databricks, or Dataflow.
• Architect, build, and maintain cloud-based data solutions using AWS, Azure, or Google Cloud Platform (GCP).
• Optimize cloud infrastructure for cost, performance, and security.
• Implement monitoring, logging, and alerting solutions for data pipelines and cloud infrastructure.

Qualifications:

• Bachelor's degree in data science, Analytics, Business, or a related field; advanced degrees or certifications are a plus.

Skills and Experience:

• Strong analytical thinking and problem-solving skills, with the ability to provide actionable insights.
• Proficient in cloud platforms: AWS (S3, EC2, EMR, Glue, Lambda), Azure (Data Factory, Blob Storage, HDInsight), or GCP (Big Query, Dataflow, Pub/Sub).
• Strong programming skills in Python, Java, Scala, or SQL.
• Experience with big data tools (Hadoop, Spark, Kafka, etc.) and ETL processes.
• Knowledge of various databases such as PostgreSQL, MongoDB, and Cassandra.

Language Requirements:

• Not specified in the job listing.

This position offers an exciting opportunity to contribute to data-driven projects in a hybrid work environment while being part of a diverse and innovative team at Capgemini.