Data Engineer (Gen AI)

Capgemini's 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. Join our team as a Data Engineer and take on a crucial role in building and optimizing data infrastructure.

Your responsibilities will include developing scalable data pipelines, ensuring data integrity, and collaborating with cross-functional teams to enhance data-driven decision-making.

Key Responsibilities:

• Programming Proficiency: Python, Scala, Java, with experience in Apache Spark & Hadoop.
• Database Expertise: Hands-on with SQL & NoSQL (MySQL, PostgreSQL, MongoDB, Cassandra).
• ETL & Data Warehousing: Skilled in data modeling, transformation, and processing.
• Machine Learning Integration: Understands data needs for AI model training.
• Pipeline Development: Experience with Apache Airflow, Luigi, and workflow automation.
• Big Data Technologies: Knowledge of data lakes, real-time processing, and streaming solutions.
• Scalable Data Architecture: Design robust, high-performance data solutions.
• Collaboration & Innovation: Work closely with ML engineers & explore new technologies.
• Version Control & Documentation: Proficient in Git, GitLab, and code management.

Ideal Candidate Profile:

• Expertise in AI & ML: Proficiency in machine learning, NLP, and deep learning.
• Strong Communication Skills: Ability to present complex AI concepts to non-technical stakeholders.
• Problem-Solving Mindset: Innovative thinker with a solutions-driven approach.
• Collaborative Team Player: Experienced in cross-functional teamwork.
• Agile Experience: Preferred background in Agile methodologies.
• Educational Background: Bachelor's in Computer Science, Data Science, IT, or a related field with a focus on data engineering and big data technologies.

Consider joining Capgemini to accelerate your career while contributing to a more sustainable and inclusive future.