Data Engineer with Data Formats

at  Capgemini

CAPGEMINI IS A GLOBAL BUSINESS AND TECHNOLOGY TRANSFORMATION PARTNER, HELPING ORGANIZATIONS TO ACCELERATE THEIR DUAL TRANSITION TO A DIGITAL AND SUSTAINABLE WORLD WHILE CREATING TANGIBLE IMPACT FOR ENTERPRISES AND SOCIETY. IT IS A RESPONSIBLE AND DIVERSE GROUP OF 350,000 TEAM MEMBERS IN MORE THAN 50 COUNTRIES. WITH ITS STRONG OVER 55-YEAR HERITAGE, CAPGEMINI IS TRUSTED BY ITS CLIENTS TO UNLOCK THE VALUE OF TECHNOLOGY TO ADDRESS THE ENTIRE BREADTH OF THEIR BUSINESS NEEDS. IT DELIVERS END-TO-END SERVICES AND SOLUTIONS LEVERAGING STRENGTHS FROM STRATEGY AND DESIGN TO ENGINEERING, ALL FUELED BY ITS MARKET-LEADING CAPABILITIES IN AI, CLOUD, AND DATA, COMBINED WITH ITS DEEP INDUSTRY EXPERTISE AND PARTNER ECOSYSTEM. THE GROUP REPORTED 2023 GLOBAL REVENUES OF €22.5 BILLION.

Get The Future You Want | www.capgemini.co

WE ARE SEEKING A HIGHLY SKILLED AND EXPERIENCED DATA ENGINEER TO JOIN OUR DYNAMIC TEAM. THE IDEAL CANDIDATE WILL HAVE A DEEP UNDERSTANDING OF DATA ENGINEERING PRINCIPLES, DATA TECHNOLOGIES, AND A PROVEN TRACK RECORD OF DESIGNING AND BUILDING COMPLEX DATA PIPELINES. THIS ROLE REQUIRES STRONG EXPERTISE IN SQL, VARIOUS DATA FORMATS, PYTHON, AND JAVASCRIPT TO SUPPORT OUR DATA-DRIVEN DECISION-MAKING PROCESSES AND ENHANCE OUR DATA INFRASTRUCTURE.

• Architect and maintain scalable data pipelines using various programming technologies.
• Use SQL to query, transform, and process data across relational and NoSQL databases.
• Integrate data from APIs, flat files, and streaming sources for consistency and quality.
• Implement real-time data processing using Kafka or Solace.
• Manage data storage in systems and warehouses, optimizing for performance.
• Design data models and apply techniques like partitioning and indexing for efficiency.
• Handle multiple data formats (CSV, JSON, Parquet) and manage unstructured data.
• Utilize Python and JavaScript (Node.js) for data processing, automation, and ETL development.
• Leverage Microsoft technologies, Apache Spark, and Airflow for distributed computing.
• Implement DevOps tools (Jenkins, Git, Docker) for CI/CD and monitor pipeline performance.