Data Engineer Intern

About SiFi SiFi is a fast-growing B2B FinTech company specializing in spend management and card issuance solutions. We help businesses manage their spending, streamline expense workflows, and operate more efficiently through technology-driven financial solutions. Role Overview We are looking for a motivated Data Engineering Intern to join our team in Riyadh and gain hands-on experience building and maintaining reliable data pipelines and data models. You will work closely with experienced engineers on data infrastructure, analytics, and AI/ML initiatives that support SiFi’s fintech products and business operations. This is an excellent opportunity for someone with strong SQL fundamentals and an interest in cloud data platforms, data warehousing, and modern data engineering practices. Key Responsibilities • Assist in developing and maintaining ETL/ELT pipelines to collect, process, and transform data. • Write and optimize SQL queries for data processing and analysis. • Support data warehouse design, development, and maintenance. • Assist with data modeling, including fact tables, dimension tables, and slowly changing dimensions (SCD Type 2). • Gain exposure to cloud data platforms, preferably Google Cloud Platform (GCP) and BigQuery. • Work with transformation tools such as dbt or SQLMesh. • Support data quality checks, testing, monitoring, and pipeline observability. • Assist in implementing CI/CD practices for data pipelines and models. • Explore how AI/ML data pipelines are deployed and maintained in production. • Follow data governance, documentation, and best practices for reliable data management. Requirements Requirements • Strong fundamentals in SQL and relational databases. • Basic understanding of ETL/ELT concepts and data pipeline workflows. • Familiarity with data warehousing and data modeling concepts. • Basic knowledge of Python is an advantage. • Exposure to GCP, BigQuery, dbt, or SQLMesh through coursework, projects, or internships is a plus. • Understanding of data quality, testing, and version control concepts is beneficial. • Strong analytical, problem-solving, and learning skills. • Ability to work collaboratively in a team environment. • Currently pursuing or recently completed a degree in Computer Science, Information Technology, Data Engineering, or a related field. Show more Show less

Strong fundamentals in SQL and relational databases. Basic understanding of ETL/ELT concepts and data pipeline workflows. Familiarity with data warehousing and data modeling concepts. Basic knowledge of Python is an advantage. Exposure to GCP, BigQuery, dbt, or SQLMesh through coursework, projects, or internships is a plus. Understanding of data quality, testing, and version control concepts is beneficial. Strong analytical, problem-solving, and learning skills. Ability to work collaboratively in a team environment. Currently pursuing or recently completed a degree in Computer Science, Information Technology, Data Engineering, or a related field.

Assist in developing and maintaining ETL/ELT pipelines to collect, process, and transform data. Write and optimize SQL queries for data processing and analysis. Support data warehouse design, development, and maintenance. Assist with data modeling, including fact tables, dimension tables, and slowly changing dimensions (SCD Type 2). Gain exposure to cloud data platforms, preferably Google Cloud Platform (GCP) and BigQuery. Work with transformation tools such as dbt or SQLMesh. Support data quality checks, testing, monitoring, and pipeline observability. Assist in implementing CI/CD practices for data pipelines and models. Explore how AI/ML data pipelines are deployed and maintained in production. Follow data governance, documentation, and best practices for reliable data management.