Data Engineer - Riyadh

About Mozn

Mozn is a rapidly growing technology firm revolutionizing the field of Artificial Intelligence and Data Science headquartered in Riyadh, Saudi Arabia and it’s working to realize Vision 2030 with a proven track record of excellence in supporting and growing the tech ecosystem in Saudi Arabia and the GCC region. Mozn is the trusted AI technology partner for some of the largest government organizations, as well as many large corporations and startups.

We are in an exciting stage of scaling the company to provide AI-powered products and solutions both locally and globally that ensure the growth and prosperity of our digital humanity. It is an exciting time to work in the field of AI to create a long-lasting impact.

About The Role

We are looking for a skilled Data Engineer to join our team and contribute to the development of Mozn's Text-to-SQL product, Talk to Your Data. In this role, you will be responsible for designing, building, and optimizing the data pipelines that support our AI-driven SQL generation system. You will work closely with machine learning engineers, software developers, and product managers to ensure seamless data integration, efficient query execution, and high-performance system scalability. Additionally, you will collaborate with other teams to create high-quality queries and diverse question sets that improve model accuracy and system performance.

What You'll Do

• Develop and maintain scalable data pipelines and ETL processes to support text-to-SQL model training and inference.
• Optimize SQL query generation by designing efficient database schemas, indexing strategies, and query execution plans.
• Collaborate with ML engineers to preprocess, transform, and structure large-scale datasets for AI model inference.
• Work with product, research, and domain experts to generate and curate realistic SQL queries and natural language questions that enhance the model’s ability to understand user intent.
• Monitor and enhance data pipeline performance, reliability, and scalability.
• Ensure data quality by implementing validation and logging mechanisms.
• Support real-time and batch query execution in the text-to-SQL system by optimizing database interactions.
• Stay up to date with best practices in data engineering, database optimization, and machine learning infrastructure.
  
  

Qualifications

• 3-5 years of experience in data engineering, database administration, or a similar role.
• Strong SQL skills, including query optimization, indexing, and performance tuning.
• Experience with relational databases (PostgreSQL, MySQL, SQL Server, or similar) and cloud-based data warehouses (BigQuery, Snowflake, Redshift, etc.).
• Proficiency in Python for data processing and pipeline development.
• Experience with ETL tools (Airflow, dbt, Apache NiFi, or similar).
• Experience in handling semi-structured and unstructured data (JSON, XML, Parquet, etc.).
• Strong communication skills and ability to collaborate with cross-functional teams to develop query datasets.
• Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment.
  
  

Nice-to-Have

• Understanding of Text-to-SQL models and how they interact with databases.
• Experience working with LLMs and NLP-based systems.
• Familiarity with vector databases and embedding-based retrieval methods
  
  

Benefits

Why Mozn?

• You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space.
• You will be given a lot of responsibility and trust. We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best.
• The fundamentals will be taken care of: competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best.
• You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI.
• We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves.