Data Engineering Intern (SQL)

We are looking for a motivated and curious Data Engineering Intern to join our Database & Data Engineering team. This position is designed for an entry-level candidate who is eager to take their theoretical computer science or database knowledge and apply it in a real-world corporate environment. The focus of this internship is to master core SQL concepts and learn how production data architectures are structured. You will work closely with senior engineers who will mentor you on data modelling, schema designs, and modern analytics frameworks.

Key Responsibilities

• SQL Queries & Maintenance: Support senior developers by writing, reviewing, and running standard SQL queries to extract, filter, and inspect data.
• Database Tables & Schemas: Help maintain clean database structures, update tables, and work with relational data schemas under direct guidance.
• Data Validation: Run baseline validation scripts to check data quality, flag discrepancies, and ensure standard rows and column alignment.
• Learning & Tool Exposure: Dedicate time to learning enterprise data environments, including cloud architectures, transformation workflows, and pipeline logic.
• Documentation Support: Assist in maintaining and updating data dictionaries, technical flowcharts, and schema diagrams for internal system tracking.
  
  

Required Skills And Qualifications

• Education: Currently pursuing or recently completed a degree in Computer Science, Information Technology, software engineering, or a related technical field.
• Core SQL Proficiency: Solid baseline knowledge of foundational SQL syntax (e.g., SELECT, WHERE, JOINs, GROUP BY) from coursework, personal projects, or bootcamps.
• Relational Database Foundations: A clear understanding of how database tables relate to each other, including primary keys, foreign keys, and basic table constraints.
• Problem-Solving Aptitude: A logical approach to debugging query errors and analyzing raw tabular rows.
• Communication & Collaboration: Strong interpersonal skills with an eagerness to ask questions, learn from feedback, and participate openly in team sprints.
  
  

Preferred

• Familiarity or prior exposure to cloud-based data repositories (such as Google BigQuery syntax) is a plus.
• Conceptual knowledge of ETL/ELT logic (how data is transferred from source systems to storage tables).
• Interest or basic familiarity with analytics engineering frameworks like dbt (data build tool).
• Basic knowledge of version control tools such as Git or GitHub workflows.