Data Engineer Intern – Job Description
We are looking for a motivated Data Engineer Intern to support the development of scalable data products that power analytics, reporting, and emerging AI use cases. This role is ideal for someone eager to gain hands-on experience in modern data engineering practices, including data modeling & transformation workflows.
Key Responsibilities
Data Modeling & Analytics Support:
- Assist in building and maintaining analytics data models under guidance from senior team members.
- Support the implementation of basic dimensional models
- Help organize and validate datasets used for reporting and analytics.
- Contribute to documenting data definitions, metrics, and business logic.
- Collaborate with cross-functional teams (Product, Marketing, Sales, etc.) to understand data requirements.
dbt & Transformation Development:
- Learn and contribute to transformation pipelines using dbt, including:
- Creating simple models and staging layers
- Writing basic data tests (e.g., uniqueness, null checks)
- Assisting with documentation of models and sources
- Support debugging and improving existing data transformations.
Data Quality & Platform Support
- Help monitor data pipelines and identify data quality issues.
- Assist in validating datasets and ensuring consistency across reports.
- Participate in maintaining naming conventions and documentation standards.
- Support troubleshooting of data issues alongside the team.
Python & Automation
- Write basic Python scripts for data processing, validation, or automation tasks.
- Assist in building small utilities to improve data workflows.
- Learn to integrate Python with data pipelines and APIs.
GenAI & LLM Exposure
- Assist in preparing datasets for AI use cases such as summarization or metadata generation.
Required Qualifications
- Currently pursuing or recently completed a degree in Computer Science, Data Engineering, Information Systems, or a related field.
- Basic understanding of SQL and relational databases.
- Familiarity with Python for data-related tasks.
- Understanding of fundamental data concepts (tables, joins, aggregations).
- Strong willingness to learn and work in a collaborative environment.
- Good communication and problem-solving skills.
Preferred Qualifications (Nice to Have)
- Exposure to data warehousing concepts or tools (e.g., Snowflake, BigQuery, Redshift).
- Familiarity with dbt or similar transformation tools.
- Basic understanding of data modeling concepts.
- Exposure to Git/version control.
- Interest in analytics, data platforms, or AI/ML systems.
- Awareness of GenAI or LLM concepts is a plus.
What You’ll Gain
- Hands-on experience with modern data stack tools (dbt, cloud warehouses, Python).
- Mentorship from experienced data engineers & analyst.
- Exposure to real-world data modeling, analytics, and AI use cases.
- Opportunity to contribute to impactful data products and workflows.