Data Engineering Co-op: SQL, Python & Databricks

• Support the development and maintenance of data pipelines using SQL, Python, and Spark.
• Assist with Databricks Unity Catalog migration activities, including data validation and basic permission checks.
• Help analyze Databricks usage, cost, and job performance using metrics and AI‑driven recommendations.
• Perform data access cleanup by reviewing and updating user and group permissions.
• Support data quality checks and assist in resolving data issues with guidance from senior engineers.
• Document data assets, data processes, and standard operating procedures.
• Assist the team with ad‑hoc analysis and operational support tasks as required.

• Undergraduate / Graduate students with a background in data engineering, computer science, information systems, analytics, or related disciplines.
• Strong SQL skills and basic Python knowledge for querying, transforming, and validating data.
• Basic understanding of data engineering concepts such as ETL / ELT and batch data processing.
• Familiarity with Databricks and Spark, including notebooks, jobs, and tables.
• Understanding of basic data access and governance concepts such as users, groups, and permissions.
• Strong analytical mindset to review job performance, cost metrics, and identify simple improvement opportunities.
• Good communication, documentation, and teamwork skills, with willingness to learn and receive feedback.
• Able to commit to the internship on a full‑time basis, from Aug 2026 – January 2027.

Proficient in SQL and basic Python for data querying and transformation, with a foundational understanding of data engineering concepts such as ETL/ELT. Capable of supporting data quality checks, documentation, and operational tasks while demonstrating strong analytical and communication skills.