Senior Data Engineer

Data Engineer (GenAI Infrastructure) Location: Al Khobar, KSA Work Model: Hybrid The Opportunity Are you ready to build the backbone of the next generation of AI? We are looking for a detail-oriented Data Engineer to join our team and support a transformative Generative AI (GenAI) initiative. In this role, you won't just be moving data; you will be designing and maintaining the high-performance infrastructure that powers advanced AI models for the world's leading organizations. Join a collaborative global community where you are empowered to shape your career and reimagine what's possible. Your Role As a Data Engineer within our AI practice, you will ensure our data workflows are efficient, our pipelines are reliable, and our systems are scalable. Your key responsibilities include: GenAI Optimization: Building and maintaining data lakes, warehouses, and feature stores specifically optimized for GenAI workloads. Pipeline Engineering: Designing and implementing robust ETL/ELT processes and automated workflows using tools like Apache Airflow or Luigi . Architecture Design: Developing large-scale, high-performance data architectures that support real-time data processing and streaming. Cross-Functional Collaboration: Working side-by-side with Data Scientists and ML Engineers to understand feature engineering and data augmentation requirements. Innovation: Exploring and implementing emerging tools and technologies to enhance our evolving GenAI product development. Your Skills and Experience We are looking for a technical expert who thrives in an Agile environment and has a passion for AI/ML infrastructure. Technical Requirements: Programming: Proficiency in Python is a must. Familiarity with Scala or Java is highly valued. Big Data Frameworks: Hands-on experience with Apache Spark or Hadoop. Database Mastery: Expert knowledge of SQL and NoSQL (e.g., PostgreSQL, MySQL, MongoDB, Cassandra). AI/ML Context: Solid understanding of data preparation for Machine Learning, including MLOps tools and practices ( MLflow, DVC ). Version Control: Experience managing codebases and documentation via Git or GitLab. Professional Qualities: Proven track record in data engineering, preferably within AI/ML environments. Strong problem-solving skills and a creative approach to building innovative systems. Excellent communication skills with the ability to translate complex technical concepts for non-technical stakeholders. Education: Bachelor's degree in Computer Science, Data Science, IT, or a related field. Why Join Us? Join a thriving company where technology is used to build a more sustainable and inclusive world. You'll gain the experience and connections needed to shape your future while working on projects that have a tangible global impact. Unlock the value of technology with us. Apply today.