Senior Data Engineer

Data Engineer (GenAI Infrastructure)

Location: Al Khobar, KSA

Work Model: Hybrid

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.

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.

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 No
  
  SQL (e.g., Postgre
  
  SQL, MySQL, Mongo
  
  DB, 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 Git Lab.

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.

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.