Collaborate with the data engineering team to build and improve pipelines that extract, clean, enrich, and deliver data from multiple sources
Support the development of data ingestion and ETL pipelines for new datasets
Assist in maintaining and monitoring workflows to ensure data accuracy, timeliness, and reliability
Help troubleshoot data quality, transformation, or integration issues across pipelines
Contribute to automation initiatives that improve scale and operational efficiency
Learn and apply best practices in testing, logging, and error handling
Assist with documentation for tools, systems, and engineering standards
Work with mentors and team members to continuously improve technical skills and execution

Currently enrolled in a university co-op program in Computer Science, Software Engineering, or a related field
At least one prior internship or co-op term in a technical role
Familiarity with ETL concepts and tools
Experience writing basic Python scripts and SQL queries
Strong attention to detail and willingness to learn in a collaborative environment
Strong communication skills and ability to ask questions, receive feedback, and work with mentors
Exposure to data engineering concepts such as data modeling, orchestration tools, or transformation tools
Familiarity with cloud platforms such as Google Cloud Platform or AWS
Experience with Pandas or other Python data libraries
Exposure to web scraping tools such as Playwright, Beautiful Soup, or Requests
Familiarity with validation frameworks such as Pydantic
Experience working with LLM prompt workflows such as Gemini or ChatGPT
Comfort using Git and version control workflows
Interest in construction data, geospatial data, or startup environments

Data Engineering Intern

Key skills